scholarly journals Antineuronal antibody prevalence in Alzheimer dementia

2020 ◽  
Vol 16 (S2) ◽  
Author(s):  
Peter Koertvelyessy ◽  
Bianca Teegen ◽  
Winfried Stoecker ◽  
Emrah Düzel ◽  
Wenzel Glanz ◽  
...  
2012 ◽  
Vol 11 (7) ◽  
pp. 926-932 ◽  
Author(s):  
Elena A. Kosenko ◽  
Gjumrakch Aliev ◽  
Lyudmila A. Tikhonova ◽  
Yi Li ◽  
Armenuhi C. Poghosyan ◽  
...  

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xi Huo ◽  
Jing Chen ◽  
Shigui Ruan

Abstract Background The COVID-19 outbreak in Wuhan started in December 2019 and was under control by the end of March 2020 with a total of 50,006 confirmed cases by the implementation of a series of nonpharmaceutical interventions (NPIs) including unprecedented lockdown of the city. This study analyzes the complete outbreak data from Wuhan, assesses the impact of these public health interventions, and estimates the asymptomatic, undetected and total cases for the COVID-19 outbreak in Wuhan. Methods By taking different stages of the outbreak into account, we developed a time-dependent compartmental model to describe the dynamics of disease transmission and case detection and reporting. Model coefficients were parameterized by using the reported cases and following key events and escalated control strategies. Then the model was used to calibrate the complete outbreak data by using the Monte Carlo Markov Chain (MCMC) method. Finally we used the model to estimate asymptomatic and undetected cases and approximate the overall antibody prevalence level. Results We found that the transmission rate between Jan 24 and Feb 1, 2020, was twice as large as that before the lockdown on Jan 23 and 67.6% (95% CI [0.584,0.759]) of detectable infections occurred during this period. Based on the reported estimates that around 20% of infections were asymptomatic and their transmission ability was about 70% of symptomatic ones, we estimated that there were about 14,448 asymptomatic and undetected cases (95% CI [12,364,23,254]), which yields an estimate of a total of 64,454 infected cases (95% CI [62,370,73,260]), and the overall antibody prevalence level in the population of Wuhan was 0.745% (95% CI [0.693%,0.814%]) by March 31, 2020. Conclusions We conclude that the control of the COVID-19 outbreak in Wuhan was achieved via the enforcement of a combination of multiple NPIs: the lockdown on Jan 23, the stay-at-home order on Feb 2, the massive isolation of all symptomatic individuals via newly constructed special shelter hospitals on Feb 6, and the large scale screening process on Feb 18. Our results indicate that the population in Wuhan is far away from establishing herd immunity and provide insights for other affected countries and regions in designing control strategies and planing vaccination programs.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Laith J. Abu-Raddad ◽  
Hiam Chemaitelly ◽  
Houssein H. Ayoub ◽  
Zaina Al Kanaani ◽  
Abdullatif Al Khal ◽  
...  

AbstractThe overarching objective of this study was to provide the descriptive epidemiology of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic in Qatar by addressing specific research questions through a series of national epidemiologic studies. Sources of data were the centralized and standardized national databases for SARS-CoV-2 infection. By July 10, 2020, 397,577 individuals had been tested for SARS-CoV-2 using polymerase-chain-reaction (PCR), of whom 110,986 were positive, a positivity cumulative rate of 27.9% (95% CI 27.8–28.1%). As of July 5, case severity rate, based on World Health Organization (WHO) severity classification, was 3.4% and case fatality rate was 1.4 per 1,000 persons. Age was by far the strongest predictor of severe, critical, or fatal infection. PCR positivity of nasopharyngeal/oropharyngeal swabs in a national community survey (May 6–7) including 1,307 participants was 14.9% (95% CI 11.5–19.0%); 58.5% of those testing positive were asymptomatic. Across 448 ad-hoc testing campaigns in workplaces and residential areas including 26,715 individuals, pooled mean PCR positivity was 15.6% (95% CI 13.7–17.7%). SARS-CoV-2 antibody prevalence was 24.0% (95% CI 23.3–24.6%) in 32,970 residual clinical blood specimens. Antibody prevalence was only 47.3% (95% CI 46.2–48.5%) in those who had at least one PCR positive result, but 91.3% (95% CI 89.5–92.9%) among those who were PCR positive > 3 weeks before serology testing. Qatar has experienced a large SARS-CoV-2 epidemic that is rapidly declining, apparently due to growing immunity levels in the population.


2015 ◽  
Vol 11 (7S_Part_13) ◽  
pp. P626-P626
Author(s):  
Rita Cacace ◽  
Tobi Van den Bossche ◽  
Sebastiaan Engelborghs ◽  
Mathieu Vandenbulcke ◽  
Rik Vandenberghe ◽  
...  

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Helen Ward ◽  
Christina Atchison ◽  
Matthew Whitaker ◽  
Kylie E. C. Ainslie ◽  
Joshua Elliott ◽  
...  

AbstractEngland has experienced a large outbreak of SARS-CoV-2, disproportionately affecting people from disadvantaged and ethnic minority communities. It is unclear how much of this excess is due to differences in exposure associated with structural inequalities. Here, we report from the REal-time Assessment of Community Transmission-2 (REACT-2) national study of over 100,000 people. After adjusting for test characteristics and re-weighting to the population, overall antibody prevalence is 6.0% (95% CI: 5.8-6.1). An estimated 3.4 million people had developed antibodies to SARS-CoV-2 by mid-July 2020. Prevalence is two- to three-fold higher among health and care workers compared with non-essential workers, and in people of Black or South Asian than white ethnicity, while age- and sex-specific infection fatality ratios are similar across ethnicities. Our results indicate that higher hospitalisation and mortality from COVID-19 in minority ethnic groups may reflect higher rates of infection rather than differential experience of disease or care.


2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1107.1-1107
Author(s):  
L. Gupta ◽  
P. Gaur ◽  
V. Agarwal ◽  
R. Aggarwal ◽  
R. Misra

Background:Idiopathic Inflammatory Myositis (IIM) are heterogenous, with distinct autoantibodies reflecting upon possible clinical evolution and outcomes. Ethnicity has major influence on both antibody prevalence patterns as well as phenotypic behaviours linked to them.Objectives:Thus we sought prevalence and co-existence of myositis specific autoantibodies (MSAs) and myositis associated autoantibodies (MAAs) and associated clinical characteristics in a large cohort of patients with IIM.Methods:Adult patients with a physician diagnosis of IIM as per ACR/EULAR classification criteria were investigated for the presence of MSAs/MAAs by Line immunoassay (G4, Euro-Immune, Lubeck, Germany). Anti-Nuclear Antibody (ANA) was tested by Immunofluorescence assay (IFA), and patterns in various antibody subsets explored. Prevalence and associations of different antibodies were assessed in disease subsets and clinical phenotypes.Results:MSA and MAAs were tested in 250 IIM patients (F:M 3.8:1) of median age 37 (25-47) and disease duration 6 (3-17) years. Dermatomyositis (DM) was seen in most patients 83 (33.2%) followed by overlap myositis (OM), juvenile DM, Anti-synthetase syndrome (ASS), polymyositis (PM), and cancer associated myositis (CAM). MSAs/MAAs were found in 148 (59.2%) of patients, of which 95 (64.2%) had an MSA and 53 (35.8%) had MAAs (Fig, 1A). 93 (62.8%) of autoantibody positive patients were positive for a single antibody, and only 2 (0.8%) of total had more than one MSA (Table 1).Table 1.Multiple antibodies positive upon testing for MSA and MAA by the LIANote: ** PL-7 co-exists with Ku + Pm/Scl, **PL-12 co-exists with Pm/Scl + Ro52, **SRP co-exists with Pm/Scl + Ro52The most frequently detected MSA was anti-Jo-1 (8%), with a further 9 specificities each found in 0.5–7.0% of patients. Amongst the autoantibody positive patients, 21% (n=53) had isolated MAA positivity, anti-Ro52 (33, 62.3%) being the most common, followed by anti-Pm/Scl (11, 20.8%) and anti-Ku (9, 17.0%) (Fig. 1B).Figure 1.A. MSA and MAA in Indian cohort of myositis B. ANA patterns in myositis C. MSA in ANA negative IIMOn ANA, 76.0% (172 of 226) were positive, with speckled being the most common pattern (37%,Fig. 1C). Of those ANA negative (n=54), 61% had either MSA or MAA (Fig 1D). 18 (54.6%) had autoantibodies associated with cytoplasmic patterns suggesting that cytoplasmic ANA may be underreported.Clinical presentation akin to DM was seen with all MSA except anti-SRP. PM group was heterogenous, and included ASS, OM and necrotizing phenotype (Fig. 2A). On occasion, anti-SRP, anti-Mi-2 and anti-MDA5 presented with clinical phenotype of ASS. (Fig 2A,C). Patients with ARS or anti-SAE were often clinically amyopathic (Figure 2B,C)Figure 2.A. Phenotypic associated with various antibody subsets B,C,and D. MSA/MAA in muscle weakness, rash and ILD phenotype. E. Unique feature of eye-lid edema in some patients with MDA-5 positive myositisARS were associated with mechanic’s hand (p<0.0001,OR 7.6), ILD (p<0.0001,OR 4.4), and arthritis (p=.002,OR 2.6) though there was no difference between Jo-1 and non-Jo-1 ASS. Anti-MDA-5 associated with fever (p=0.003,OR 12) and weight loss (p=0.008,OR 10.2) and unique phenotype of eye-lid edema in some adults (Figure 2E) and arthritis in children (p=0.01, OR 11.5). Anti-TIF-1ɣ associated with alopecia (p=0.007,OR 5.9) and malignancy (p= <0.0001,OR 34) in adults but not children.Conclusion:Myositis autoantibodies are seen in two-thirds IIM and identify distinct clinical subsets as well as unique phenotypes. MSA/MAA are positive in two-thirds of those negative on ANA, adding diagnostic value. MSAs are nearly always mutually exclusive and thus useful as biomarkers for diagnosis.Acknowledgments:MSA testing supported by grants from APLAR and Association of Physicians of India.Disclosure of Interests:Latika Gupta: None declared, Priyanka Gaur: None declared, Vikas Agarwal: None declared, Rohit Aggarwal Grant/research support from: Pfizer, Genentech, BMS, Mallinckrodt, Consultant of: Pfizer, Genentech, BMS, Mallinckrodt, Bristol Myers-Squibb, octapharma, CSL Behring, AstraZeneca, Corbus, Kezar, Abbvie, Ramnath Misra: None declared


Author(s):  
Sandhya Mangalore ◽  
Shiva Shanker Reddy Mukku ◽  
Sriharish Vankayalapati ◽  
Palanimuthu Thangaraju Sivakumar ◽  
Mathew Varghese

Abstract Background Phenotyping dementia is always a complex task for a clinician. There is a need for more practical biomarkers to aid clinicians. Objective The aim of the study is to investigate the shape profile of corpus callosum (CC) in different phenotypes of dementia. Materials and Methods Our study included patients who underwent neuroimaging in our facility as a part of clinical evaluation for dementia referred from Geriatric Clinic (2017–2018). We have analyzed the shape of CC and interpreted the finding using a seven-segment division. Results The sample included MPRAGE images of Alzheimer’ dementia (AD) (n = 24), posterior cortical atrophy- Alzheimer’ dementia (PCA-AD) (n = 7), behavioral variant of frontotemporal dementia (Bv-FTD) (n = 17), semantic variant frontotemporal dementia (Sv-FTD) (n = 11), progressive nonfluent aphasia (PNFA) (n = 4), Parkinson’s disease dementia (PDD) (n = 5), diffuse Lewy body dementia (n = 7), progressive supranuclear palsy (PSP) (n = 3), and corticobasal degeneration (CBD) (n = 3). We found in posterior dementias such as AD and PCA-AD that there was predominant atrophy of splenium of CC. In Bv-FTD, the genu and anterior half of the body of CC was atrophied, whereas in PNFA, PSP, PDD, and CBD there was atrophy of the body of CC giving a dumbbell like profile. Conclusion Our study findings were in agreement with the anatomical cortical regions involved in different phenotypes of dementia. Our preliminary study highlighted potential usefulness of CC in the clinical setting for phenotyping dementia in addition to clinical history and robust biomarkers.


Geriatrics ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 5
Author(s):  
Donatella Rita Petretto ◽  
Gian Pietro Carrogu ◽  
Luca Gaviano ◽  
Lorenzo Pili ◽  
Roberto Pili

Over 100 years ago, Alois Alzheimer presented the clinical signs and symptoms of what has been later called “Alzheimer Dementia” in a young woman whose name was Augustine Deter [...]


2021 ◽  
pp. 104794
Author(s):  
Christine C. Johnson ◽  
Chad M. Coleman ◽  
Alexandra R. Sitarik ◽  
Joyce E. Leon ◽  
Robert J. Tibbetts ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rupam Bhattacharyya ◽  
Ritoban Kundu ◽  
Ritwik Bhaduri ◽  
Debashree Ray ◽  
Lauren J. Beesley ◽  
...  

AbstractSusceptible-Exposed-Infected-Removed (SEIR)-type epidemiologic models, modeling unascertained infections latently, can predict unreported cases and deaths assuming perfect testing. We apply a method we developed to account for the high false negative rates of diagnostic RT-PCR tests for detecting an active SARS-CoV-2 infection in a classic SEIR model. The number of unascertained cases and false negatives being unobservable in a real study, population-based serosurveys can help validate model projections. Applying our method to training data from Delhi, India, during March 15–June 30, 2020, we estimate the underreporting factor for cases at 34–53 (deaths: 8–13) on July 10, 2020, largely consistent with the findings of the first round of serosurveys for Delhi (done during June 27–July 10, 2020) with an estimated 22.86% IgG antibody prevalence, yielding estimated underreporting factors of 30–42 for cases. Together, these imply approximately 96–98% cases in Delhi remained unreported (July 10, 2020). Updated calculations using training data during March 15-December 31, 2020 yield estimated underreporting factor for cases at 13–22 (deaths: 3–7) on January 23, 2021, which are again consistent with the latest (fifth) round of serosurveys for Delhi (done during January 15–23, 2021) with an estimated 56.13% IgG antibody prevalence, yielding an estimated range for the underreporting factor for cases at 17–21. Together, these updated estimates imply approximately 92–96% cases in Delhi remained unreported (January 23, 2021). Such model-based estimates, updated with latest data, provide a viable alternative to repeated resource-intensive serosurveys for tracking unreported cases and deaths and gauging the true extent of the pandemic.


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