Novel blood test for early biomarkers of preeclampsia and Alzheimer's disease.
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ABSTRACT:
SUBMITTER: Cheng S
PROVIDER: S-EPMC8342418 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Blood-based biomarkers for Alzheimer's disease would be very valuable because blood is a more accessible biofluid and is suitable for repeated sampling. However, currently there are no robust and reliable blood-based biomarkers for practical diagnosis. In this study we used a knowledge-based protein feature pool and two novel support vector machine embedded feature selection methods to find panels consisting of two and three biomarkers. We validated these biomarker sets using another serum cohort and an RNA profile cohort from the brain. Our panels included the proteins ECH1, NHLRC2, HOXB7, FN1, ERBB2, and SLC6A13 and demonstrated promising sensitivity (>87%), specificity (>91%), and accuracy (>89%).
| S-EPMC4932164 | biostudies-literature
Project description:Potential biomarkers for Alzheimer's disease (AD) include amyloid β1-42 (Aβ1-42), t-Tau, p-Tau181, neurofilament light chain (NFL), and neuroimaging biomarkers. Their combined use is useful for diagnosing and monitoring the progress of AD. Therefore, further development of a combination of these biomarkers is essential. We investigated whether plasma NFL/Aβ1-42 can serve as a plasma-based primary screening biomarker reflecting brain neurodegeneration and amyloid pathology in AD for monitoring disease progression and early diagnosis. We measured the NFL and Aβ1-42 concentrations in the CSF and plasma samples and performed correlation analysis to evaluate the utility of these biomarkers in the early diagnosis and monitoring of AD spectrum disease progression. Pearson's correlation analysis was used to analyse the associations between the fluid biomarkers and neuroimaging data. The study included 136 participants, classified into five groups: 28 cognitively normal individuals, 23 patients with preclinical AD, 22 amyloid-negative patients with amnestic mild cognitive impairment, 32 patients with prodromal AD, and 31 patients with AD dementia. With disease progression, the NFL concentrations increased and Aβ1-42 concentrations decreased. The plasma and CSF NFL/Aβ1-42 were strongly correlated (r = 0.558). Plasma NFL/Aβ1-42 was strongly correlated with hippocampal volume/intracranial volume (r = 0.409). In early AD, plasma NFL/Aβ1-42 was associated with higher diagnostic accuracy than the individual biomarkers. Moreover, in preclinical AD, plasma NFL/Aβ1-42 changed more rapidly than the CSF t-Tau or p-Tau181 concentrations. Our findings highlight the utility of plasma NFL/Aβ1-42 as a non-invasive plasma-based biomarker for early diagnosis and monitoring of AD spectrum disease progression.
| S-EPMC8773964 | biostudies-literature
Project description:Neurodegenerative disorders such as Alzheimer's disease (AD) represent a mounting public health challenge. As these diseases are difficult to diagnose clinically, biomarkers of underlying pathophysiology are playing an ever-increasing role in research, clinical trials, and in the clinical work-up of patients. Though cerebrospinal fluid (CSF) and positron emission tomography (PET)-based measures are available, their use is not widespread due to limitations, including high costs and perceived invasiveness. As a result of rapid advances in the development of ultra-sensitive assays, the levels of pathological brain- and AD-related proteins can now be measured in blood, with recent work showing promising results. Plasma P-tau appears to be the best candidate marker during symptomatic AD (i.e., prodromal AD and AD dementia) and preclinical AD when combined with Aβ42/Aβ40. Though not AD-specific, blood NfL appears promising for the detection of neurodegeneration and could potentially be used to detect the effects of disease-modifying therapies. This review provides an overview of the progress achieved thus far using AD blood-based biomarkers, highlighting key areas of application and unmet challenges.
| S-EPMC8749476 | biostudies-literature
Project description:To date, the development of disease-modifying therapies for Alzheimer's disease (AD) has largely focused on the removal of amyloid beta A? fragments from the CNS. Proteomic profiling of patient fluids may help identify novel therapeutic targets and biomarkers associated with AD pathology. Here, we applied the Olink™ ProSeek immunoassay to measure 270 CSF and plasma proteins across 415 A?- negative cognitively normal individuals (A?- CN), 142 A?-positive CN (A?+?CN), 50 A?- mild cognitive impairment (MCI) patients, 75 A?+?MCI patients, and 161 A?+?AD patients from the Swedish BioFINDER study. A validation cohort included 59 A?- CN, 23 A?-?+?CN, 44 A?- MCI and 53 A?+?MCI. To compare protein concentrations in patients versus controls, we applied multiple linear regressions adjusting for age, gender, medications, smoking and mean subject-level protein concentration, and corrected findings for false discovery rate (FDR, q?<?0.05). We identified, and replicated, altered levels of ten CSF proteins in A?+?individuals, including CHIT1, SMOC2, MMP-10, LDLR, CD200, EIF4EBP1, ALCAM, RGMB, tPA and STAMBP (-?0.14?<?d?<?1.16; q?<?0.05). We also identified and replicated alterations of six plasma proteins in A?+ individuals OSM, MMP-9, HAGH, CD200, AXIN1, and uPA (-?0.77?<?d?<?1.28; q?<?0.05). Multiple analytes associated with cognitive performance and cortical thickness (q?<?0.05). Plasma biomarkers could distinguish AD dementia (AUC?=?0.94, 95% CI?=?0.87-0.98) and prodromal AD (AUC?=?0.78, 95% CI?=?0.68-0.87) from CN. These findings reemphasize the contributions of immune markers, phospholipids, angiogenic proteins and other biomarkers downstream of, and potentially orthogonal to, A?- and tau in AD, and identify candidate biomarkers for earlier detection of neurodegeneration.
| S-EPMC6836495 | biostudies-literature
Project description:The definitive diagnosis of Alzheimer's Disease (AD) without the need for neuropathological confirmation remains a challenge in AD research today, despite efforts to uncover the molecular and biological underpinnings of the disease process. Furthermore, the potential for therapeutic intervention is limited upon the onset of symptoms, providing motivation for studying and treating the AD precursor mild cognitive impairment (MCI), the prodromal stage of AD instead. Applying machine learning classification to transcriptomic data of MCI, AD, and cognitively normal (CN) control patients, we identified differentially expressed genes that serve as biomarkers for the characterization and classification of subjects into MCI or AD groups. Predictive models employing these biomarker genes exhibited good classification performances for CN, MCI, and AD, significantly above random chance. The PI3K-Akt, IL-17, JAK-STAT, TNF, and Ras signaling pathways were also enriched in these biomarker genes, indicating their diagnostic potential and pathophysiological roles in MCI and AD. These findings could aid in the recognition of MCI and AD risk in clinical settings, allow for the tracking of disease progression over time in individuals as part of a therapeutic approach, and provide possible personalized drug targets for early intervention of MCI and AD.
| S-EPMC9309434 | biostudies-literature
Project description:BackgroundIdeally, disease modifying therapies for Alzheimer disease (AD) will be applied during the 'preclinical' stage (pathology present with cognition intact) before severe neuronal damage occurs, or upon recognizing very mild cognitive impairment. Developing and judiciously administering such therapies will require biomarker panels to identify early AD pathology, classify disease stage, monitor pathological progression, and predict cognitive decline. To discover such biomarkers, we measured AD-associated changes in the cerebrospinal fluid (CSF) proteome.Methods and findingsCSF samples from individuals with mild AD (Clinical Dementia Rating [CDR] 1) (n?=?24) and cognitively normal controls (CDR 0) (n?=?24) were subjected to two-dimensional difference-in-gel electrophoresis. Within 119 differentially-abundant gel features, mass spectrometry (LC-MS/MS) identified 47 proteins. For validation, eleven proteins were re-evaluated by enzyme-linked immunosorbent assays (ELISA). Six of these assays (NrCAM, YKL-40, chromogranin A, carnosinase I, transthyretin, cystatin C) distinguished CDR 1 and CDR 0 groups and were subsequently applied (with tau, p-tau181 and A?42 ELISAs) to a larger independent cohort (n?=?292) that included individuals with very mild dementia (CDR 0.5). Receiver-operating characteristic curve analyses using stepwise logistic regression yielded optimal biomarker combinations to distinguish CDR 0 from CDR>0 (tau, YKL-40, NrCAM) and CDR 1 from CDR<1 (tau, chromogranin A, carnosinase I) with areas under the curve of 0.90 (0.85-0.94 95% confidence interval [CI]) and 0.88 (0.81-0.94 CI), respectively.ConclusionsFour novel CSF biomarkers for AD (NrCAM, YKL-40, chromogranin A, carnosinase I) can improve the diagnostic accuracy of A?42 and tau. Together, these six markers describe six clinicopathological stages from cognitive normalcy to mild dementia, including stages defined by increased risk of cognitive decline. Such a panel might improve clinical trial efficiency by guiding subject enrollment and monitoring disease progression. Further studies will be required to validate this panel and evaluate its potential for distinguishing AD from other dementing conditions.
| S-EPMC3020224 | biostudies-literature
Project description:Background: Preeclampsia (PE) is a placental disease characterized by hypertension and proteinuria in pregnant women, which is associated with a high maternal and infantile morbidity. However, circulating biomarkers able to predict the prognosis of PE are lacking. Methods: Thirty-eight women were included in the study. They consisted of 19 patients with PE (13 with severe PE and 6 women with non-severe PE) and 19 gestational age-matched normal pregnancy controls. We measured coagulation pathway, endothelial responses and microparticle release and circulating gene expression in PE patient groups and normotensive controls. Results: The measurement of markers associated with coagulation pathway, endothelial activation and circulating microparticles enabled to discriminate PE from normal pregnancy but were not sufficient to distinguish severe from non-severe PE. PE patients also exhibited a specific transcriptional program distinct from that of control women and subtle differences were observed between severe and non-severe PE. Functional annotation of the up-modulated signature in PE highlighted two main functions related to ribosome and complement. Importantly, we found that 8 genes were specifically up-modulated in severe preeclampsia. Among these genes, the expression of VSIG4 was significantly increased in patients with severe preeclampsia in comparison with controls and patients with non-severe preeclampsia. Conclusion: Using transcriptional signatures of blood samples, we identified the gene encoding the estrogen receptor as a potential diagnostic marker of severe preeclampsia. In addition, the determination of this gene may improve the prognostic assessment of severe preeclampsia. Thirty-eight women were included in the study: 19 patients with PE, including 6 women with non-severe PE and 13 with severe PE, and 19 women with normal pregnancy (NP) selected according to age, weight, smoking status, race, gestational age at the inclusion, and blood pH (Table 1 of manuscript). Women with NP had no history of medical illness or medication, and received routing prenatal care. The diagnostic of PE was based on a blood pressure of M-bM-^IM-% 140/90 mmHg taken twice, uricemia above normal laboratory range (120-420 M-BM-5mol/L), and proteinuria higher than 300 mg in a 24 hour-collection, occurring after 20 gestational weeks in previously normotensive women (Table 2). The criteria used to define severe PE included one of the following conditions: a blood pressure higher than 160/110 mmHg, a proteinuria higher than 1500 mg/24h), a multisystem disorder, maternal cerebral symptoms (seizures, stroke) or intrauterine growth restriction below the 3M-BM-0 percentile. Women with multiple gestations, fetal congenital malformations/chromosomal abnormalities, recent infection, antiphospholipid antibodies, trauma, drug or alcohol abuse during pregnancy, preexisting hypertension, thrombophilia with PE history, or women receiving anticoagulant or antiaggregation therapy were excluded from the study. Two microarrays (one non-severe PE and one normal) were discarded from the analysis for technical reasons. Thus, only 36 microarrays are included here.
2014-05-14 | E-GEOD-48424 | biostudies-arrayexpress
Project description:The complexity of Alzheimer's disease (AD) and its long prodromal phase poses challenges for early diagnosis and yet allows for the possibility of the development of disease modifying treatments for secondary prevention. It is, therefore, of importance to develop biomarkers, in particular, in the preclinical or early phases that reflect the pathological characteristics of the disease and, moreover, could be of utility in triaging subjects for preventative therapeutic clinical trials. Much research has sought biomarkers for diagnostic purposes by comparing affected people to unaffected controls. However, given that AD pathology precedes disease onset, a pathology endophenotype design for biomarker discovery creates the opportunity for detection of much earlier markers of disease. Blood-based biomarkers potentially provide a minimally invasive option for this purpose and research in the field has adopted various "omics" approaches in order to achieve this. This review will, therefore, examine the current literature regarding blood-based proteomic biomarkers of AD and its associated pathology.
| S-EPMC4644785 | biostudies-literature
Project description:Background: At present, the main diagnostic methods for Alzheimer's disease (AD) are positron emission tomography (PET) scanning of the brain and analysis of cerebrospinal fluid (CSF) sample, but these methods are expensive and harmful to patients. Recently, more researchers focus on diagnosing AD by detecting biomarkers in blood, which is a cheaper and harmless way. Therefore, identifying AD-related proteins in blood can help treatment and diagnosis. Methods: We proposed a hypothesis that similar diseases share similar proteins. Diseases with similar symptoms are caused by abnormalities of similar proteins. Assuming that the similarities between AD and other diseases obey the normal distribution, we developed an iterative method based on disease similarity (IBDS). We combined Elastic Network (EN) with Minimum angle regression (MAR) to find the optimal solution. Finally, we used case studies and Summary data Mendelian Random (SMR) to verify our method. Results: We selected 39 diseases which are highly related to AD. They correspond 1,481 kinds of proteins. One hundred and eighty-four proteins are reported to be related to AD in Uniprot and the number would be 284 with our method. The AUC of our method by cross-validation is 0.9251 which is much higher than previous methods. Conclusion: In this paper, we presented a novel method for prioritizing AD-related proteins. Seven proteins have tissue specificity in blood among these 284 proteins, which could be used to diagnose AD in future. Case studies and SMR have been used to prove the relationship between these 7 proteins and AD. Availability and Implementation: https://github.com/zty2009/Identifying-Protein-Biomarkers-in-Blood-for-Alzheimer-s-Disease.
| S-EPMC7314983 | biostudies-literature
Project description:Background: Preeclampsia (PE) is a placental disease characterized by hypertension and proteinuria in pregnant women, which is associated with a high maternal and infantile morbidity. However, circulating biomarkers able to predict the prognosis of PE are lacking. Methods: Thirty-eight women were included in the study. They consisted of 19 patients with PE (13 with severe PE and 6 women with non-severe PE) and 19 gestational age-matched normal pregnancy controls. We measured coagulation pathway, endothelial responses and microparticle release and circulating gene expression in PE patient groups and normotensive controls. Results: The measurement of markers associated with coagulation pathway, endothelial activation and circulating microparticles enabled to discriminate PE from normal pregnancy but were not sufficient to distinguish severe from non-severe PE. PE patients also exhibited a specific transcriptional program distinct from that of control women and subtle differences were observed between severe and non-severe PE. Functional annotation of the up-modulated signature in PE highlighted two main functions related to ribosome and complement. Importantly, we found that 8 genes were specifically up-modulated in severe preeclampsia. Among these genes, the expression of VSIG4 was significantly increased in patients with severe preeclampsia in comparison with controls and patients with non-severe preeclampsia. Conclusion: Using transcriptional signatures of blood samples, we identified the gene encoding the estrogen receptor as a potential diagnostic marker of severe preeclampsia. In addition, the determination of this gene may improve the prognostic assessment of severe preeclampsia.
2014-05-14 | GSE48424 | GEO