Lipid-driven CFTR clustering is impaired in cystic fibrosis and restored by corrector drugs.

Membrane proteins often cluster in nanoscale membrane domains (lipid rafts) that coalesce into ceramide-rich platforms during cell stress, however the clustering mechanisms remain uncertain. The cystic fibrosis transmembrane conductance regulator (CFTR), which is mutated in cystic fibrosis (CF), forms clusters that are cholesterol dependent and become incorporated into long-lived platforms during hormonal stimulation. We report here that clustering does not involve known tethering interactions of CFTR with PDZ domain proteins, filamin A or the actin cytoskeleton. It also does not require CFTR palmitoylation but is critically dependent on membrane lipid order and is induced by detergents that increase the phase separation of membrane lipids. Clustering and integration of CFTR into ceramide-rich platforms are abolished by the disease mutations F508del and S13F and rescued by the CFTR modulators elexacaftor plus tezacaftor. These results indicate CF therapeutics that correct mutant protein folding restore both trafficking and normal lipid interactions in the plasma membrane. This article has an associated First Person interview with the first author of the paper.

The Association of the Glymphatic Function with Parkinson's Disease Symptoms: Neuroimaging Evidence from Longitudinal and Cross-Sectional Studies.

OBJECTIVE: Emerging pathological evidence suggests that there is an association between glymphatic dysfunction and the progression of Parkinson's disease (PD). However, the clinical evidence of this association remains lacking. METHODS: In this study, the index for diffusion tensor image analysis along the perivascular space (ALPS index) was calculated to evaluate glymphatic function. RESULTS: Overall, 289 patients with PD were enrolled in the cross-sectional study. The ALPS index was found to be negatively correlated with age, disease severity, and dyskinesia. In the longitudinal study, the information on a total of 95 PD patients with 5-year follow-up examinations was collected from the Parkinson's Progression Marker Initiative, 33 of which were classified into the low ALPS index group, and all others were classified into the mid-high ALPS index group based on the first tertile of the baseline ALPS index. The results of longitudinal regression indicated that there was a significant main group effect on autonomic dysfunction, as well as on activities of daily living. In addition, the low ALPS index group had faster deterioration in MDS-UPDRS part III and part II, Symbol Digit Modalities Test and Hopkins Verbal Learning Test. Path analysis showed that ALPS index acted as a significant mediator between tTau/ Aß1-42 and cognitive change in the Symbol Digit Modalities Test score at year 4 and year 5. INTERPRETATION: The ALPS index, an neuroimaging marker of glymphatic function, is correlated with PD disease severity, motor symptoms, and autonomic function, and is predictive of faster deterioration in motor symptoms and cognitive function. Additionally, glymphatic function may mediate the pathological role of toxic protein in cognitive decline. ANN NEUROL 2023;94:672-683.

Ionocyte-Specific Regulation of Cystic Fibrosis Transmembrane Conductance Regulator.

CFTR (cystic fibrosis transmembrane conductance regulator) is a tightly regulated anion channel that mediates chloride and bicarbonate conductance in many epithelia and in other tissues, but whether its regulation varies depending on the cell type has not been investigated. Epithelial CFTR expression is highest in rare cells called ionocytes. We studied CFTR regulation in control and ionocyte-enriched cultures by transducing bronchial basal cells with adenoviruses that encode only eGFP or FOXI1 (forkhead box I1) + eGFP as separate polypeptides. FOXI1 dramatically increased the number of transcripts for ionocyte markers ASCL3 (Achaete-Scute Family BHLH Transcription Factor 3), BSND, ATP6V1G3, ATP6V0D2, KCNMA1, and CFTR without altering those for secretory (SCGB1A1), basal (KRT5, KRT6, TP63), goblet (MUC5AC), or ciliated (FOXJ1) cells. The number of cells displaying strong FOXI1 expression was increased 7-fold, and there was no evidence for a broad increase in background immunofluorescence. Total CFTR mRNA and protein levels increased 10-fold and 2.5-fold, respectively. Ionocyte-enriched cultures displayed elevated basal current, increased adenylyl cyclase 5 expression, and tonic suppression of CFTR activity by the phosphodiesterase PDE1C, which has not been shown previously to regulate CFTR activity. The results indicate that CFTR regulation depends on cell type and identifies PDE1C as a potential target for therapeutics that aim to increase CFTR function specifically in ionocytes.

Comparing machine learning-derived MRI-based and blood-based neurodegeneration biomarkers in predicting syndromal conversion in early AD.

INTRODUCTION: We compared the machine learning-derived, MRI-based Alzheimer's disease (AD) resemblance atrophy index (AD-RAI) with plasma neurofilament light chain (NfL) level in predicting conversion of early AD among cognitively unimpaired (CU) and mild cognitive impairment (MCI) subjects. METHODS: We recruited participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) who had the following data: clinical features (age, gender, education, Montreal Cognitive Assessment [MoCA]), structural MRI, plasma biomarkers (p-tau181 , NfL), cerebrospinal fluid biomarkers (CSF) (Aß42, p-tau181 ), and apolipoprotein E (APOE) ε4 genotype. We defined AD using CSF Aß42 (A+) and p-tau181 (T+). We defined conversion (C+) if a subject progressed to the next syndromal stage within 4 years. RESULTS: Of 589 participants, 96 (16.3%) were A+T+C+. AD-RAI performed better than plasma NfL when added on top of clinical features, plasma p-tau181 , and APOE ε4 genotype (area under the curve [AUC] = 0.832 vs. AUC = 0.650 among CU, AUC = 0.853 vs. AUC = 0.805 among MCI) in predicting A+T+C+. DISCUSSION: AD-RAI outperformed plasma NfL in predicting syndromal conversion of early AD. HIGHLIGHTS: AD-RAI outperformed plasma NfL in predicting syndromal conversion among early AD. AD-RAI showed better metrics than volumetric hippocampal measures in predicting syndromal conversion. Combining clinical features, plasma p-tau181 and apolipoprotein E (APOE) with AD-RAI is the best model for predicting syndromal conversion.

Anosmia, mild cognitive impairment, and biomarkers of brain aging in older adults.

Olfactory impairment is a potential marker for prodromal dementia, but the underlying mechanisms are poorly understood. This population-based study included 4214 dementia-free participants (age ≥65 years). Olfaction was assessed using the 16-item Sniffin' Sticks identification test. In the subsamples, we measured plasma amyloid beta (Aß)40, Aß42, total tau, and neurofilament light chain (NfL; n = 1054); and quantified hippocampal, entorhinal cortex, and white matter hyperintensity (WMH) volumes, and Alzheimer's disease (AD)-signature cortical thickness (n = 917). Data were analyzed with logistic and linear regression models. In the total sample, mild cognitive impairment (MCI) was diagnosed in 1102 persons (26.2%; amnestic MCI, n = 931; non-amnestic MCI, n = 171). Olfactory impairment was significantly associated with increased likelihoods of MCI, amnestic MCI, and non-amnestic MCI. In the subsamples, anosmia was significantly associated with higher plasma total tau and NfL concentrations, smaller hippocampal and entorhinal cortex volumes, and greater WMH volume, and marginally with lower AD-signature cortical thickness. These results suggest that cerebral neurodegenerative and microvascular lesions are common neuropathologies linking anosmia with MCI in older adults.

Automated brain volumetric measures with AccuBrain: version comparison in accuracy, reproducibility and application for diagnosis.

BACKGROUND: Automated brain volumetry has been widely used to assess brain volumetric changes that may indicate clinical states and progression. Among the tools that implement automated brain volumetry, AccuBrain has been validated for its accuracy, reliability and clinical applications for the older version (IV1.2). Here, we aim to investigate the performance of an updated version (IV2.0) of AccuBrain for future use from several aspects. METHODS: Public datasets with 3D T1-weighted scans were included for version comparisons, each with Alzheimer's disease (AD) patients and normal control (NC) subjects that were matched in age and gender. For the comparisons of the brain volumetric measures quantified from the same scans, we investigated the difference of hippocampal segmentation accuracy (using Dice similarity coefficient [DSC] as the major measurement). As AccuBrain generates a composite index (AD resemblance atrophy index, AD-RAI) that indicates similarity with AD-like brain atrophy pattern, we also compared the two versions for the diagnostic accuracy of AD versus NC with AD-RAI. Also, we examined the intra-scanner reproducibility of the two versions for the scans acquired with short-intervals using intraclass correlation coefficient. RESULTS: AccuBrain IV2.0 presented significantly higher accuracy of hippocampal segmentation (DSC: 0.91 vs. 0.89, p < 0.001) and diagnostic accuracy of AD (AUC: 0.977 vs. 0.921, p < 0.001) than IV1.2. The results of intra-scanner reproducibility did not favor one version over the other. CONCLUSIONS: AccuBrain IV2.0 presented better segmentation accuracy and diagnostic accuracy of AD, and similar intra-scanner reproducibility compared with IV1.2. Both versions should be feasible for use due to the small magnitude of differences.

High-density lipoprotein cholesterol and brain aging amongst rural-dwelling older adults: a population-based magnetic resonance imaging study.

BACKGROUND AND PURPOSE: Current evidence supports the involvement of lipids in brain aging. A range of serum lipids is explored in association with brain structure and cognitive function amongst rural-dwelling older adults. METHODS: This population-based cross-sectional study included 184 rural-dwelling adults (age ≥ 65 years, 39.1% women) in Shandong, China. In 2014-2016, data on demographics, lifestyle, health conditions and serum lipids were collected. Volumes of gray matter, white matter, ventricles, hippocampus and white matter hyperintensity were automatically estimated on brain magnetic resonance imaging. Global cognitive function was assessed with the Mini-Mental State Examination (MMSE), and mild cognitive impairment (MCI) was defined according to Petersen's criteria. Data were analyzed using the general linear regression, logistic regression and mediation models. RESULTS: Of the 184 participants, 47 were defined with MCI. Low high-density lipoprotein cholesterol (HDL-C; <1.55 vs. ≥1.55 mmol/l) was significantly associated with reduced volumes of total white matter (multi-adjusted ß = -9.77, 95% confidence interval -19.48-0.06) and hippocampus (-0.23, -0.46-0.01), a lower MMSE score (-1.49, -2.67-0.31) and a higher likelihood of MCI (multi-adjusted odds ratio 3.21, 95% confidence interval 1.42-7.29). The mediation effects of structural brain measures on the associations between a low level of HDL-C and MMSE score or MCI were not statistically significant (p > 0.05). CONCLUSIONS: This study suggests that low HDL-C may be involved in structural brain aging and cognitive dysfunction amongst rural-dwelling older adults in China, but the association of low HDL-C with cognitive aging phenotypes appears not to be mediated by brain structure.

The dual phosphodiesterase 3/4 inhibitor RPL554 stimulates rare class III and IV CFTR mutants.

Over 2,000 mutations have been reported in the cystic fibrosis transmembrane conductance regulator (cftr) gene, many of which cause disease but are rare and have no effective treatment. Thus, there is an unmet need for new, mutation-agnostic therapies for cystic fibrosis (CF). Phosphodiesterase (PDE) inhibitors are one such class of therapeutics that have been shown to elevate intracellular cAMP levels and stimulate CFTR-dependent anion secretion in human airway epithelia; however, the number of people with CF that could be helped by PDE inhibitors remains to be determined. Here we used Fisher rat thyroid (FRT) cells stably transduced with rare human CFTR mutants and studied their responsiveness to the dual phosphodiesterase 3/4 inhibitor RPL554 (Verona Pharma). Through its inhibitory effect on PDE4D, we find that RPL554 can elevate intracellular cAMP leading to a potentiation of forskolin-stimulated current mediated by R334W, T338I, G551D, and S549R mutants of CFTR when used alone or in combination with CFTR modulators. We also were able to reproduce these effects of RPL554 on G551D-CFTR when it was expressed in primary human bronchial epithelial cells, indicating that RPL554 would have stimulatory effects on rare CFTR mutants in human airways and validating FRT cells as a model for PDE inhibitor studies. Furthermore, we provide biochemical evidence that VX-809 causes surprisingly robust correction of several class III and IV CFTR mutants. Together, our findings further support the therapeutic potential of RPL554 for patients with CF with class III/IV mutations and emphasize the potential of PDEs as potential drug targets that could benefit patients with CF.

Dynamic changes of views on the brain changes of Cushing's syndrome using different computer-assisted tool.

Cushing's syndrome (CS) provides a unique model for assessing the neurotoxic effect of chronic hypercortisolism on human brains. With the ongoing development of different computer-assisted tools, four research stages emerged, each with its own pearls and pitfalls. This review summarizes current knowledge and describes the dynamic changes of views on the brain changes of CS, especially in the current era of the rapid development of artificial intelligence and big data. The adverse effects of GC on brain are proven to be on structural, functional and cellular levels at the same time.

A quantitative MRI index for assessing the severity of hippocampal sclerosis in temporal lobe epilepsy.

BACKGROUND: Hippocampal sclerosis (HS) is associated with post-surgery outcome in patients with temporal lobe epilepsy (TLE), and an automated method that quantifies HS severity is still lacking. Here, we aim to propose an MRI-based HS index (HSI) that integrates hippocampal volume and FLAIR signal to measure the severity of HS. METHODS: Forty-two pre-surgery TLE patients were included retrospectively, with T1-weighted (T1W) and FLAIR images acquired from each subject. Two experienced neurosurgeons (W.D. and C.S.) and one neurologist (Q.L.) rated HS severity with a four-class grading scale (normal, mild, moderate and severe) based on both hippocampal volume loss and increased FLAIR signal. A consensus of HS severity for each subject was made by voting among the three visual rating results. Regarding the automatic quantification, the hippocampal volume was quantified by AccuBrain on T1W image, and the FLAIR signal of hippocampus was calculated as the mean intensity of hippocampal region on the FLAIR image (normalized by the mean intensity of gray matter). To fit the HSI from visual rating, we applied ordinal regression with the voted visual rating as the dependent variable, and hippocampal volume and FLAIR signal as the independent variables. The HSI was calculated by weighting the predicted probabilities of the four-class grading scales from ordinal regression. RESULTS: The intra-class correlation coefficient (single measure) of the three raters was 0.806. The generated HSI was significantly correlated with the visual rating scales of the three raters (W.D.: 0.823, Q.L.: 0.817, C.S.: 0.717). HSI scores well differentiated the different HS categories as defined by the agreed HS visual rating (normal vs. mild: p < 0.001, mild vs. moderate: p < 0.001, moderate vs. severe: p = 0.001). CONCLUSIONS: The proposed HSI was consistent with visual rating scales from epileptologists and sensitive to HS severity. This MRI-based index may help to evaluate HS severity in clinical practice. Further validations are needed to associate HSI with post-surgery outcomes.

Automated Brain MRI Volumetry Differentiates Early Stages of Alzheimer's Disease From Normal Aging.

As an enrichment strategy supplemented by the diagnostic framework of subjective cognitive decline (SCD), SCD plus identifies features that may increase the likelihood of including future-Alzheimer's disease (AD) patients. This study aimed to identify the shared and distinct atrophy patterns between patients specified by SCD plus and amnestic mild cognitive impairment (aMCI, a prodromal stage of AD) and to investigate the extent that automated brain magnetic resonance imaging (MRI) volumetry can differentiate patients with SCD from normal control (NC) participants and patients with aMCI. We acquired structural MRI brain scans from 44 patients with aMCI, 40 patients with SCD (who met the major criteria of SCD plus), and 48 NC participants. Automatic brain segmentation was performed to quantify the volumetric measures of cognitive-relevant areas. These volumetric measures were compared across the 3 groups with analysis of variance. In addition, we performed support vector machine analyses using volumetric measures of single regions or multiple regions to further evaluate the sensitivity of automated brain volumetry in differentiating a specific group from another. The atrophy patterns in patients with aMCI and SCD were similar. Using the regional volumetric measures, we achieved high performance in differentiating aMCI and SCD from NCs (average classification accuracy [ACC] > 90%). However, the performance was not ideal when differentiating aMCI from SCD (ACC < 63%). In conclusion, patients with SCD specified by SCD plus presented similar atrophy patterns as patients with aMCI, which was distinguishable from NC participants. Future studies should aim to associate the atrophy patterns of SCD with possible conversion to aMCI or AD in a longitudinal design.

Standardization of hippocampus volumetry using automated brain structure volumetry tool for an initial Alzheimer's disease imaging biomarker.

BACKGROUND: One significant barrier to incorporate Alzheimer's disease (AD) imaging biomarkers into diagnostic criteria is the lack of standardized methods for biomarker quantification. The European Alzheimer's Disease Consortium-Alzheimer's Disease Neuroimaging Initiative (EADC-ADNI) Harmonization Protocol project provides the most authoritative guideline for hippocampal definition and has produced a manually segmented reference dataset for validation of automated methods. PURPOSE: To validate automated hippocampal volumetry using AccuBrain™, against the EADC-ADNI dataset, and assess its diagnostic performance for differentiating AD and normal aging in an independent cohort. MATERIAL AND METHODS: The EADC-ADNI reference dataset comprise of manually segmented hippocampal labels from 135 volumetric T1-weighted scans from various scanners. Dice similarity coefficient (DSC), intraclass correlation coefficient (ICC), and Pearson's r were obtained for AccuBrain™ and FreeSurfer. The magnetic resonance imaging (MRI) of a separate cohort of 299 individuals (150 normal controls, 149 with AD) were obtained from the ADNI database and processed with AccuBrain™ to assess its diagnostic accuracy. Area under the curve (AUC) for total hippocampal volumes (HV) and hippocampal fraction (HF) were determined. RESULTS: Compared with EADC-ADNI dataset ground truths, AccuBrain™ had a mean DSC of 0.89/0.89/0.89, ICC of 0.94/0.96/0.95, and r of 0.95/0.96/0.95 for right/left/total HV. AccuBrain™ HV and HF had AUC of 0.76 and 0.80, respectively. Thresholds of ≤ 5.71 mL and ≤ 0.38% afforded 80% sensitivity for AD detection. CONCLUSION: AccuBrain™ provides accurate automated hippocampus segmentation in accordance with the EADC-ADNI standard, with great potential value in assisting clinical diagnosis of AD.

Efficacy and Safety of Renal Sympathetic Denervation on Dogs with Pressure Overload-Induced Heart Failure.

BACKGROUND: In dogs with heart failure (HF) induced by overload pressure, the role of renal sympathetic denervation (RSD) on heart failure and in the renal artery is unclear. Therefore, we investigated the efficacy and safety of RSD in dogs with pressure overload-induced heart failure. METHODS: Twenty mongrel dogs were divided into a sham-operated group, an HF group and an HF + RSD group. In the sham-operated group, the abdominal aorta was located but was not constricted, in the HF group, the abdominal aorta was constricted without RSD, and the HF+RSD group underwent RSD with constriction of the abdominal aorta after 10 weeks. Blood sampling assays, echocardiography, intravascular ultrasound (IVUS) measurement and histopathological examination were performed. RESULTS: Renal sympathetic denervation caused a significant reduction in the levels of noradrenaline (166.62±6.84 vs. 183.48±13.66 pg/ml, P<0.05), plasma renin activity (1.93±0.12 vs. 2.10±0.13 ng/mlh, P<0.05) and B-type natriuretic peptide (71.14±3.86 vs. 83.15±5.73 pg/ml, P<0.05) at eight weeks after RSD in the HF+RSD group. Compared with the HF group at eight weeks, the left ventricular internal dimension at end-diastole and end-systole were lower and the left ventricular ejection fraction was higher (all P<0.05) at eight weeks after RSD in the HF+RSD group. Intravenous ultrasound images showed no changes in the renal artery lumen, and intimal hyperplasia and vascular lumen stenosis were not observed after RSD. CONCLUSIONS: Renal sympathetic denervation could improve cardiac function in dogs with HF induced by pressure overload; RSD had no adverse influence on the renal artery.

Tractography atlas-based spatial statistics: Statistical analysis of diffusion tensor image along fiber pathways.

The quantitative analysis of diffusion tensor image (DTI) data has attracted increasing attention in recent decades for studying white matter (WM) integrity and development. Among the current DTI analysis methods, tract-based spatial statistics (TBSS), as a pioneering approach for the voxelwise analysis of DTI data, has gained a lot of popularity due to its user-friendly framework. However, in recent years, the reliability and interpretability of TBSS have been challenged by several works, and several improvements over the original TBSS pipeline have been suggested. In this paper, we propose a new DTI statistical analysis method, named tractography atlas-based spatial statistics (TABSS). It doesn't rely on the accurate alignment of fractional anisotropy (FA) images for population analysis and gets rid of the skeletonization procedures of TBSS, which have been indicated as the major sources of error. Furthermore, TABSS improves the interpretability of results by directly reporting the resulting statistics on WM tracts, waiving the need of a WM atlas in the interpretation of the results. The feasibility of TABSS was evaluated in an example study to show age-related FA alternation pattern of healthy human brain. Through this preliminary study, it is validated that TABSS can provide detailed statistical results in a comprehensive and easy-to-understand way.

Histogram-based normalization technique on human brain magnetic resonance images from different acquisitions.

BACKGROUND: Intensity normalization is an important preprocessing step in brain magnetic resonance image (MRI) analysis. During MR image acquisition, different scanners or parameters would be used for scanning different subjects or the same subject at a different time, which may result in large intensity variations. This intensity variation will greatly undermine the performance of subsequent MRI processing and population analysis, such as image registration, segmentation, and tissue volume measurement. METHODS: In this work, we proposed a new histogram normalization method to reduce the intensity variation between MRIs obtained from different acquisitions. In our experiment, we scanned each subject twice on two different scanners using different imaging parameters. With noise estimation, the image with lower noise level was determined and treated as the high-quality reference image. Then the histogram of the low-quality image was normalized to the histogram of the high-quality image. The normalization algorithm includes two main steps: (1) intensity scaling (IS), where, for the high-quality reference image, the intensities of the image are first rescaled to a range between the low intensity region (LIR) value and the high intensity region (HIR) value; and (2) histogram normalization (HN),where the histogram of low-quality image as input image is stretched to match the histogram of the reference image, so that the intensity range in the normalized image will also lie between LIR and HIR. RESULTS: We performed three sets of experiments to evaluate the proposed method, i.e., image registration, segmentation, and tissue volume measurement, and compared this with the existing intensity normalization method. It is then possible to validate that our histogram normalization framework can achieve better results in all the experiments. It is also demonstrated that the brain template with normalization preprocessing is of higher quality than the template with no normalization processing. CONCLUSIONS: We have proposed a histogram-based MRI intensity normalization method. The method can normalize scans which were acquired on different MRI units. We have validated that the method can greatly improve the image analysis performance. Furthermore, it is demonstrated that with the help of our normalization method, we can create a higher quality Chinese brain template.

Role of tyrosine phosphorylation in the muscarinic activation of the cystic fibrosis transmembrane conductance regulator (CFTR).

Cystic fibrosis transmembrane conductance regulator (CFTR) is a chloride (Cl(-)) channel, which plays an important role in physiological anion and fluid secretion, and is defective in several diseases. Although its activation by PKA and PKC has been studied extensively, its regulation by receptors is less well understood. To study signaling involved in CFTR activation, we measured whole-cell Cl(-) currents in BHK cells cotransfected with GPCRs and CFTR. In cells expressing the M3 muscarinic acetylcholine receptor, the agonist carbachol (Cch) caused strong activation of CFTR through two pathways; the canonical PKA-dependent mechanism and a second mechanism that involves tyrosine phosphorylation. The role of PKA was suggested by partial inhibition of cholinergic stimulation by the specific PKA inhibitor Rp-cAMPS. The role of tyrosine kinases was suggested by Cch stimulation of 15SA-CFTR and 9CA-CFTR, mutants that lack 15 PKA or 9 PKC consensus sequences and are unresponsive to PKA or PKC stimulation, respectively. Moreover the residual Cch response was sensitive to inhibitors of the Pyk2 and Src tyrosine kinase family. Our results suggest that tyrosine phosphorylation acts on CFTR directly and through inhibition of the phosphatase PP2A. Results suggest that PKA and tyrosine kinases contribute to CFTR regulation by GPCRs that are expressed at the apical membrane of intestinal and airway epithelia.

Intensity and sulci landmark combined brain atlas construction for Chinese pediatric population.

Constructing an atlas from a population of brain images is of vital importance to medical image analysis. Especially in neuroscience study, creating a brain atlas is useful for intra- and inter-population comparison. Research on brain atlas construction has attracted great attention in recent years, but the research on pediatric population is still limited, mainly due to the limited availability and the relatively low quality of pediatric magnetic resonance brain images. This article is targeted at creating a high quality representative brain atlas for Chinese pediatric population. To achieve this goal, we have designed a set of preprocessing procedures to improve the image quality and developed an intensity and sulci landmark combined groupwise registration method to align the population of images for atlas construction. As demonstrated in experiments, the newly constructed atlas can better represent the size and shape of brains of Chinese pediatric population, and show better performance in Chinese pediatric brain image analysis compared with other standard atlases.

Machine Learning-Derived MRI-Based Neurodegeneration Biomarker for Alzheimer's Disease: A Multi-Database Validation Study.

BACKGROUND: Pilot study showed that Alzheimer's disease resemblance atrophy index (AD-RAI), a machine learning-derived MRI-based neurodegeneration biomarker of AD, achieved excellent diagnostic performance in diagnosing AD with moderate to severe dementia. OBJECTIVE: The primary objective was to validate and compare the performance of AD-RAI with conventional volumetric hippocampal measures in diagnosing AD with mild dementia. The secondary objectives were 1) to investigate the association between imaging biomarkers with age and gender among cognitively unimpaired (CU) participants; 2) to analyze whether the performance of differentiating AD with mild dementia from CU will improve after adjustment for age/gender. METHODS: AD with mild dementia (n = 218) and CU (n = 1,060) participants from 4 databases were included. We investigated the area under curve (AUC), sensitivity, specificity, and balanced accuracy of AD-RAI, hippocampal volume (HV), and hippocampal fraction (HF) in differentiating between AD and CU participants. Among amyloid-negative CU participants, we further analyzed correlation between the biomarkers with age/gender. We also investigated whether adjustment for age/gender will affect performance. RESULTS: The AUC of AD-RAI (0.93) was significantly higher than that of HV (0.89) and HF (0.89). Subgroup analysis among A + AD and A- CU showed that AUC of AD-RAI (0.97) was also higher than HV (0.94) and HF (0.93). Diagnostic performance of AD-RAI and HF was not affected by age/gender while that of HV improved after age adjustment. CONCLUSIONS: AD-RAI achieves excellent clinical validity and outperforms conventional volumetric hippocampal measures in aiding the diagnosis of AD mild dementia without the need for age adjustment.

Associations of Serum Liver Function with Cerebral Blood Flow in Patients with Alzheimer's Disease.

Background: Increasing evidence suggests that both amyloid-ß metabolism disorders in the liver and cerebral hypoperfusion play an important role in the pathogenesis of Alzheimer's disease (AD). However, the relevance of liver function alterations to cerebral blood flow (CBF) of patients with AD remains unclear. Objective: We aimed to investigate the associations between liver function changes and CBF of patients with AD. Methods: We recruited 17 patients with sporadic AD. In addition to physical and neurological examinations, detection of AD biomarkers in cerebrospinal fluid by enzyme-linked immunosorbent assay and CBF assessment by arterial spin labeling sequence of magnetic resonance image scans as well as measure of liver function markers in serum by routine laboratory testing were conducted. Neuropsychological tests were evaluated, including Mini-Mental State Examination and Montreal Cognitive Assessment. Linear and rank correlations were performed to test the associations of liver function alterations with regional CBF of AD. Results: We found that liver function markers, especially total protein, the ratio of albumin to globin, globin, alkaline phosphatase, and aspartate aminotransferase were significantly associated with regional CBF of AD patients. Conclusions: These findings demonstrated significant associations between perfusion in certain brain regions of AD and alterations of liver function markers, particularly proteins and liver enzymes, which might provide implications to the pathogenesis and treatment of AD.

Associations of apolipoprotein E ε4 allele, regional cerebral blood flow, and serum liver function markers in patients with cognitive impairment.

Introduction: The ε4 allele of the apolipoprotein E gene (APOE4) is expressed abundantly in both the brain and peripheral circulation as a genetic risk factor for Alzheimer's disease (AD). Cerebral blood flow (CBF) dysfunction is an essential feature of AD, and the liver plays an important role in the pathogenesis of dementia. However, the associations of APOE4 with CBF and liver function markers in patients with cognitive impairment remains unclear. We aimed to evaluate the associations of APOE4 with CBF measured by arterial spin labeling (ASL) magnetic resonance imaging (MRI) and serum liver function markers in participants who were diagnosed with cognitive impairment. Methods: Fourteen participants with AD and sixteen with amnestic mild cognitive impairment (MCI) were recruited. In addition to providing comprehensive clinical information, all patients underwent laboratory tests and MRI. All participants were divided into carriers and noncarriers of the ε4 allele, and T-tests and Mann-Whitney U tests were used to observe the differences between APOE4 carriers and noncarriers in CBF and liver function markers. Results: Regarding regional cerebral blood flow (rCBF), APOE4 carriers showed hyperperfusion in the bilateral occipital cortex, bilateral thalamus, and left precuneus and hypoperfusion in the right lateral temporal cortex when compared with noncarriers. Regarding serum liver function markers, bilirubin levels (including total, direct, and indirect) were lower in APOE4 carriers than in noncarriers. Conclusion: APOE4 exerts a strong effect on CBF dysfunction by inheritance, representing a risk factor for AD. APOE4 may be related to bilirubin metabolism, potentially providing specific neural targets for the diagnosis and treatment of AD.