Disparity of smell tests in Alzheimer's disease and other neurodegenerative disorders: a systematic review and meta-analysis.

Background: There are discrepancies of olfactory impairment between Alzheimer's disease (AD) and other neurodegenerative disorders. Olfactory deficits may be a potential marker for early and differential diagnosis of AD. We aimed to assess olfactory functions in patients with AD and other neurodegenerative disorders, to further evaluate the smell tests using subgroup analysis, and to explore moderating factors affecting olfactory performance. Methods: Cross-sectional studies relating to olfactory assessment for both AD and other neurodegenerative disorders published before 27 July 2022 in English, were searched on PubMed, Embase and Cochrane. After literature screening and quality assessment, meta-analyses were conducted using stata14.0 software. Results: Forty-two articles involving 12 smell tests that evaluated 2,569 AD patients were included. It was revealed that smell tests could distinguish AD from mild cognitive impairment (MCI), Lewy body disease (LBD), depression, and vascular dementia (VaD), but not from diseases such as frontotemporal dementia (FTD). Our finding indicated that in discriminating AD from MCI, the University of Pennsylvania Smell Identification Test (UPSIT) was most frequently used (95%CI: -1.12 to -0.89), while the Brief Smell Identification Test (B-SIT), was the most widely used method in AD vs. LBD group. Further subgroup analyses indicated that the methods of smell test used contributed to the heterogeneity in olfactory threshold and discrimination scores in group AD vs. MCI. While the moderating variables including age, MMSE scores, education years in AD vs. LBD, were account for heterogeneity across studies. Conclusion: Our finding suggests smell tests have potential value in early differential diagnosis of AD. UPSIT and its simplified variant, B-SIT, are widely used methods in the analyses. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/display_record.php? RecordID = 357970 (PROSPERO, registration number CRD42022357970).

ER-mitochondrial contact protein Miga regulates autophagy through Atg14 and Uvrag.

Mitochondrial malfunction and autophagy defects are often concurrent phenomena associated with neurodegeneration. We show that Miga, a mitochondrial outer-membrane protein that regulates endoplasmic reticulum-mitochondrial contact sites (ERMCSs), is required for autophagy. Loss of Miga results in an accumulation of autophagy markers and substrates, whereas PI3P and Syx17 levels are reduced. Further experiments indicated that the fusion between autophagosomes and lysosomes is defective in Miga mutants. Miga binds to Atg14 and Uvrag; concordantly, Miga overexpression results in Atg14 and Uvrag recruitment to mitochondria. The heightened PI3K activity induced by Miga requires Uvrag, whereas Miga-mediated stabilization of Syx17 is dependent on Atg14. Miga-regulated ERMCSs are critical for PI3P formation but are not essential for the stabilization of Syx17. In summary, we identify a mitochondrial protein that regulates autophagy by recruiting two alternative components of the PI3K complex present at the ERMCSs.

Predicting Thioflavin Fluorescence of Retinal Amyloid Deposits Associated With Alzheimer's Disease from Their Polarimetric Properties.

Purpose: To use machine learning in those with brain amyloid to predict thioflavin fluorescence (indicative of amyloid) of retinal deposits from their interactions with polarized light. Methods: We imaged 933 retinal deposits in 28 subjects with post mortem evidence of brain amyloid using thioflavin fluorescence and polarization sensitive microscopy. Means and standard deviations of 14 polarimetric properties were input to machine learning algorithms. Two oversampling strategies were applied to overcome data imbalance. Three machine learning algorithms: linear discriminant analysis, supporting vector machine, and random forest (RF) were trained to predict thioflavin positive deposits. For each method; accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve were computed. Results: For the polarimetric positive deposits, using 1 oversampling method, RF had the highest area under the receiver operating characteristic curve (0.986), which was not different from that with the second oversampling method. RF had 95% accuracy, 94% sensitivity, and 97% specificity. After including deposits with no polarimetric signals, polarimetry correctly predicted 93% of thioflavin positive deposits. Linear retardance and linear anisotropy were the dominant polarimetric properties in RF with 1 oversampling method, and no polarimetric properties were dominant in the second method. Conclusions: Thioflavin positivity of retinal amyloid deposits can be predicted from their images in polarized light. Polarimetry is a promising dye-free method of detecting amyloid deposits in ex vivo retinal tissue. Further testing is required for translation to live eye imaging. Translational Relevance: This dye-free method distinguishes retinal amyloid deposits, a promising biomarker of Alzheimer's disease, in human retinas imaged with polarimetry.

Miga-mediated endoplasmic reticulum-mitochondria contact sites regulate neuronal homeostasis.

Endoplasmic reticulum (ER)-mitochondria contact sites (ERMCSs) are crucial for multiple cellular processes such as calcium signaling, lipid transport, and mitochondrial dynamics. However, the molecular organization, functions, regulation of ERMCS, and the physiological roles of altered ERMCSs are not fully understood in higher eukaryotes. We found that Miga, a mitochondrion located protein, markedly increases ERMCSs and causes severe neurodegeneration upon overexpression in fly eyes. Miga interacts with an ER protein Vap33 through its FFAT-like motif and an amyotrophic lateral sclerosis (ALS) disease related Vap33 mutation considerably reduces its interaction with Miga. Multiple serine residues inside and near the Miga FFAT motif were phosphorylated, which is required for its interaction with Vap33 and Miga-mediated ERMCS formation. The interaction between Vap33 and Miga promoted further phosphorylation of upstream serine/threonine clusters, which fine-tuned Miga activity. Protein kinases CKI and CaMKII contribute to Miga hyperphosphorylation. MIGA2, encoded by the miga mammalian ortholog, has conserved functions in mammalian cells. We propose a model that shows Miga interacts with Vap33 to mediate ERMCSs and excessive ERMCSs lead to neurodegeneration.