Identification of new biomarkers for Down's syndrome in maternal plasma

Transthyretin mutagenesis: impact on amyloidogenesis and disease

Transthyretin (TTR), a homotetrameric protein found in plasma, cerebrospinal fluid, and the eye, plays a pivotal role in the onset of several amyloid diseases with high morbidity and mortality. Protein aggregation and fibril formation by wild-type TTR and its natural more amyloidogenic variants are hallmarks of ATTRwt and ATTRv amyloidosis, respectively. The formation of soluble amyloid aggregates and the accumulation of insoluble amyloid fibrils and deposits in multiple tissues can lead to organ dysfunction and cell death. The most frequent manifestations of ATTR are polyneuropathies and cardiomyopathies. However, clinical manifestations such as carpal tunnel syndrome, leptomeningeal, and ocular amyloidosis, among several others may also occur. This review provides an up-to-date listing of all single amino-acid mutations in TTR known to date. Of approximately 220 single-point mutations, 93% are considered pathogenic. Aspartic acid is the residue mutated with the highest frequency, whereas tryptophan is highly conserved. "Hot spot" mutation regions are mainly assigned to β-strands B, C, and D. This manuscript also reviews the protein aggregation models that have been proposed for TTR amyloid fibril formation and the transient conformational states that convert native TTR into aggregation-prone molecular species. Finally, it compiles the various in vitro TTR aggregation protocols currently in use for research and drug development purposes. In short, this article reviews and discusses TTR mutagenesis and amyloidogenesis, and their implications in disease onset.

Novel Multiplexed Plasma Biomarker Panel Has Diagnostic and Prognostic Potential in Children With Hypertrophic Cardiomyopathy

BACKGROUND

Hypertrophic cardiomyopathy (HCM) is defined clinically by pathological left ventricular hypertrophy. We have previously developed a plasma proteomics biomarker panel that correlates with clinical markers of disease severity and sudden cardiac death risk in adult patients with HCM. The aim of this study was to investigate the utility of adult biomarkers and perform new discoveries in proteomics for childhood-onset HCM.

METHODS

Fifty-nine protein biomarkers were identified from an exploratory plasma proteomics screen in children with HCM and augmented into our existing multiplexed targeted liquid chromatography-tandem/mass spectrometry-based assay. The association of these biomarkers with clinical phenotypes and outcomes was prospectively tested in plasma collected from 148 children with HCM and 50 healthy controls. Machine learning techniques were used to develop novel pediatric plasma proteomic biomarker panels.

RESULTS

Four previously identified adult HCM markers (aldolase fructose-bisphosphate A, complement C3a, talin-1, and thrombospondin 1) and 3 new markers (glycogen phosphorylase B, lipoprotein a and profilin 1) were elevated in pediatric HCM. Using supervised machine learning applied to training (n=137) and validation cohorts (n=61), this 7-biomarker panel differentiated HCM from healthy controls with an area under the curve of 1.0 in the training data set (sensitivity 100% [95% CI, 95-100]; specificity 100% [95% CI, 96-100]) and 0.82 in the validation data set (sensitivity 75% [95% CI, 59-86]; specificity 88% [95% CI, 75-94]). Reduced circulating levels of 4 other peptides (apolipoprotein L1, complement 5b, immunoglobulin heavy constant epsilon, and serum amyloid A4) found in children with high sudden cardiac death risk provided complete separation from the low and intermediate risk groups and predicted mortality and adverse arrhythmic outcomes (hazard ratio, 2.04 [95% CI, 1.0-4.2]; P=0.044).

CONCLUSIONS

In children, a 7-biomarker proteomics panel can distinguish HCM from controls with high sensitivity and specificity, and another 4-biomarker panel identifies those at high risk of adverse arrhythmic outcomes, including sudden cardiac death.

Steroid profile analysis by liquid chromatography-tandem mass spectrometry in second-trimester pregnant women for trisomy 21 screening

BACKGROUND

Trisomy 21 is a serious chromosome abnormality. The conventional Down's screening test is the most widely used for trisomy 21 screening. However, this method could lead to a higher false positive rate. Therefore, we aim to analyze steroid profile in second-trimester pregnant women and identify novel serum biomarkers of trisomy 21.

METHODS

We employed an LC-MS/MS method to measure the steroid profile. The concentrations and product-to-substrate ratios in 71 second-trimester pregnant women were determined and statistically analyzed to identify novel biomarkers for trisomy 21 screening.

RESULTS

We found that there were significant differences in levels of E3, 11-deoxycortisol, and 11-deoxycortisol /17-hydroxyprogesterone between two groups. The OPLS-DA plots revealed obvious separation between two groups. Combining VIP analysis (VIP > 1.0) with volcano plot (P < 0.05 and fold change >1.2 or < 0.83), 11-deoxycortisol was identified as a novel biomarker for trisomy 21. After controlling for confounders, we found 11-deoxycortisol was associated with trisomy 21 (adjusted P = 0.009), and the fully adjusted OR (95 % CI) was 0.098 (0.016-0.593) in highest quartile versus lowest quartile of 11-deoxycortisol (P = 0.011).

CONCLUSIONS

Steroid profile analysis for the first time showed that steroid hormones perturbations occurred in pregnant women carrying a fetus affected by trisomy 21 and decreased 11-deoxycortisol levels were associated with trisomy 21.

Identification of a Multiplex Biomarker Panel for Hypertrophic Cardiomyopathy Using Quantitative Proteomics and Machine Learning

Hypertrophic cardiomyopathy (HCM) is defined by pathological left ventricular hypertrophy (LVH). It is the commonest inherited cardiac condition and a significant number of high risk cases still go undetected until a sudden cardiac death (SCD) event. Plasma biomarkers do not currently feature in the assessment of HCM disease progression, which is tracked by serial imaging, or in SCD risk stratification, which is based on imaging parameters and patient/family history. There is a need for new HCM plasma biomarkers to refine disease monitoring and improve patient risk stratification. To identify new plasma biomarkers for patients with HCM, we performed exploratory myocardial and plasma proteomics screens and subsequently developed a multiplexed targeted liquid chromatography-tandem/mass spectrometry-based assay to validate the 26 peptide biomarkers that were identified. The association of discovered biomarkers with clinical phenotypes was prospectively tested in plasma from 110 HCM patients with LVH (LVH+ HCM), 97 controls, and 16 HCM sarcomere gene mutation carriers before the development of LVH (subclinical HCM). Six peptides (aldolase fructose-bisphosphate A, complement C3, glutathione S-transferase omega 1, Ras suppressor protein 1, talin 1, and thrombospondin 1) were increased significantly in the plasma of LVH+ HCM compared with controls and correlated with imaging markers of phenotype severity: LV wall thickness, mass, and percentage myocardial scar on cardiovascular magnetic resonance imaging. Using supervised machine learning (ML), this six-biomarker panel differentiated between LVH+ HCM and controls, with an area under the curve of ≥ 0.87. Five of these peptides were also significantly increased in subclinical HCM compared with controls. In LVH+ HCM, the six-marker panel correlated with the presence of nonsustained ventricular tachycardia and the estimated five-year risk of sudden cardiac death. Using quantitative proteomic approaches, we have discovered six potentially useful circulating plasma biomarkers related to myocardial substrate changes in HCM, which correlate with the estimated sudden cardiac death risk.

CSF pro-orexin and amyloid-β38 expression in Alzheimer's disease and frontotemporal dementia

There is an unmet need for markers that can stratify different forms and subtypes of dementia. Because of similarities in clinical presentation, it can be difficult to distinguish between Alzheimer's disease (AD) and frontotemporal dementia (FTD). Using a multiplex targeted proteomic LC-MS/MS platform, we aimed to identify cerebrospinal fluid proteins differentially expressed between patients with AD and FTD. Furthermore analysis of 2 confirmed FTD genetic subtypes carrying progranulin (GRN) and chromosome 9 open reading frame 72 (C9orf72) mutations was performed to give an insight into the differing pathologies of these forms of FTD. Patients with AD (n = 13) demonstrated a significant (p < 0.007) 1.24-fold increase in pro-orexin compared to FTD (n = 32). Amyloid beta-38 levels in patients with AD were unaltered but demonstrated a >2-fold reduction (p < 0.0001) in the FTD group compared to controls and a similar 1.83-fold reduction compared to the AD group (p < 0.001). Soluble TREM2 was elevated in both dementia groups but did not show any difference between AD and FTD. A further analysis comparing FTD subgroups revealed slightly lower levels of proteins apolipoprotein E, CD166, osteopontin, transthyretin, and cystatin C in the GRN group (n = 9) compared to the C9orf72 group (n = 7). These proteins imply GRN FTD elicits an altered inflammatory response to C9orf72 FTD.

Disturbance of redox homeostasis in Down Syndrome: Role of iron dysmetabolism

Down Syndrome (DS) is the most common genetic form of intellectual disability that leads in the majority of cases to development of early-onset Alzheimer-like dementia (AD). The neuropathology of DS has several common features with AD including alteration of redox homeostasis, mitochondrial deficits, and inflammation among others. Interestingly, some of the genes encoded by chromosome 21 are responsible of increased oxidative stress (OS) conditions that are further exacerbated by decreased antioxidant defense. Previous studies from our groups showed that accumulation of oxidative damage is an early event in DS neurodegeneration and that oxidative modifications of selected proteins affects the integrity of the protein degradative systems, antioxidant response, neuronal integrity and energy metabolism. In particular, the current review elaborates recent findings demonstrating the accumulation of oxidative damage in DS and we focus attention on specific deregulation of iron metabolism, which affects both the central nervous system and the periphery. Iron dysmetabolism is a well-recognized factor that contributes to neurodegeneration; thus we opine that better understanding how and to what extent the concerted loss of iron dyshomeostasis and increased OS occur in DS could provide novel insights for the development of therapeutic strategies for the treatment of Alzheimer-like dementia.

Global serum glycoform profiling for the investigation of dystroglycanopathies & Congenital Disorders of Glycosylation

The Congenital Disorders of Glycosylation (CDG) are an expanding group of genetic disorders which encompass a spectrum of glycosylation defects of protein and lipids, including N- & O-linked defects and among the latter are the muscular dystroglycanopathies (MD). Initial screening of CDG is usually based on the investigation of the glycoproteins transferrin, and/or apolipoprotein CIII. These biomarkers do not always detect complex or subtle defects present in older patients, therefore there is a need to investigate additional glycoproteins in some cases. We describe a sensitive 2D-Differential Gel Electrophoresis (DIGE) method that provides a global analysis of the serum glycoproteome. Patient samples from PMM2-CDG (n = 5), CDG-II (n = 7), MD and known complex N- & O-linked glycosylation defects (n = 3) were analysed by 2D DIGE. Using this technique we demonstrated characteristic changes in mass and charge in PMM2-CDG and in charge in CDG-II for α1-antitrypsin, α1-antichymotrypsin, α2-HS-glycoprotein, ceruloplasmin, and α1-acid glycoproteins 1&2. Analysis of the samples with known N- & O-linked defects identified a lower molecular weight glycoform of C1-esterase inhibitor that was not observed in the N-linked glycosylation disorders indicating the change is likely due to affected O-glycosylation. In addition, we could identify abnormal serum glycoproteins in LARGE and B3GALNT2-deficient muscular dystrophies. The results demonstrate that the glycoform pattern is varied for some CDG patients not all glycoproteins are consistently affected and analysis of more than one protein in complex cases is warranted. 2D DIGE is an ideal method to investigate the global glycoproteome and is a potentially powerful tool and secondary test for aiding the complex diagnosis and sub classification of CDG. The technique has further potential in monitoring patients for future treatment strategies. In an era of shifting emphasis from gel- to mass-spectral based proteomics techniques, we demonstrate that 2D-DIGE remains a powerful method for studying global changes in post-translational modifications of proteins.

Screening and identification of potential predictive biomarkers for Down's syndrome from second trimester maternal serum

OBJECTIVE

In this study, we aimed to search for noninvasive predictive biomarkers for prenatal diagnosis of Down's syndrome (DS).

METHODS

Maternal serum samples from five DS-affected pregnant women and five DS-unaffected women were analyzed by 2D gel electrophoresis and MALDI-TOF mass spectrometry to screen for potential predictive biomarkers of DS. Then, differential levels of dGTPase, β2-glycoprotein I (β2-GPI), complement factor H-related protein 1 precursor (CFHR1) and kininogen 1 isoform 2 were further verified by western blotting tests in another independent group.

RESULTS

Statistical analysis results revealed 29 protein spots whose levels differed significantly in the DS-affected pregnancies group. Of these, the eight most differentially expressed in DP were identified successfully. Among these, levels of dGTPase, CFHR1 and kininogen 1 were elevated significantly, whereas β2-GPI was reduced in DP.

DISCUSSION

These preliminarily verified proteins might serve as potential predictive biomarkers for DS-affected pregnancies.

Unraveling the complexity of neurodegeneration in brains of subjects with Down syndrome: insights from proteomics

Down syndrome (DS) is one of the most common genetic causes of intellectual disability characterized by multiple pathological phenotypes, among which neurodegeneration is a key feature. The neuropathology of DS is complex and likely results from impaired mitochondrial function, increased oxidative stress, and altered proteostasis. After the age of 40 years, many (most) DS individuals develop a type of dementia that closely resembles that of Alzheimer's disease with deposition of senile plaques and neurofibrillary tangles. A number of studies demonstrated that increased oxidative damage, accumulation of damaged/misfolded protein aggregates, and dysfunction of intracellular degradative systems are critical events in the neurodegenerative processes. This review summarizes the current knowledge that demonstrates a “chronic” condition of oxidative stress in DS pointing to the putative molecular pathways that could contribute to accelerate cognition and memory decline. Proteomics and redox proteomics studies are powerful tools to unravel the complexity of DS phenotypes, by allowing to identifying protein expression changes and oxidative PTMs that are proved to be detrimental for protein function. It is reasonable to suggest that changes in the cellular redox status in DS neurons, early from the fetal period, could provide a fertile environment upon which increased aging favors neurodegeneration. Thus, after a critical age, DS neuropathology can be considered a human model of early Alzheimer's disease and could contribute to understanding the overlapping mechanisms that lead from normal aging to development of dementia.

Growth associated protein (GAP-43): cloning and the development of a sensitive ELISA for neurological disorders

GAP-43 has been studied in the rodent and mammalian brain and shown to be present specifically in areas undergoing axonal elongation and synapse formation. GAP-43 was cloned using the baculovirus expression system and purified. A sandwich ELISA was developed using the recombinant GAP-43 as standard and validated. CSF GAP-43 levels were analysed in benign intracranial hypertension, movement disorders, multiple sclerosis, neuropathy, CNS infections, motor neuron disease, and headache (neurological controls). GAP-43 levels were low in all disorders analysed (in particular motor neuron disease; p=0.001, and movement disorders and multiple sclerosis; p<0.0001) compared to controls, aside from CNS infections. GAP-43 is preferentially reduced in the CSF of neurological disorders associated with neurodegeneration.

Qualitative and quantitative characterization of plasma proteins when incorporating traveling wave ion mobility into a liquid chromatography-mass spectrometry workflow for biomarker discovery: use of product ion quantitation as an alternative data analysis tool for label free quantitation

Discovery of protein biomarkers in clinical samples necessitates significant prefractionation prior to liquid chromatography-mass spectrometry (LC-MS) analysis. Integrating traveling wave ion mobility spectrometry (TWIMS) enables in-line gas phase separation which when coupled with nanoflow liquid chromatography and data independent acquisition tandem mass spectrometry, confers significant advantages to the discovery of protein biomarkers by improving separation and inherent sensitivity. Incorporation of TWIMS leads to a packet of concentrated ions which ultimately provides a significant improvement in sensitivity. As a consequence of ion packeting, when present at high concentrations, accurate quantitation of proteins can be affected due to detector saturation effects. Human plasma was analyzed in triplicate using liquid-chromatography data independent acquisition mass spectrometry (LC-DIA-MS) and using liquid-chromatography ion-mobility data independent acquisition mass spectrometry (LC-IM-DIA-MS). The inclusion of TWIMS was assessed for the effect on sample throughput, data integrity, confidence of protein and peptide identification, and dynamic range. The number of identified proteins is significantly increased by an average of 84% while both the precursor and product mass accuracies are maintained between the modalities. Sample dynamic range is also maintained while quantitation is achieved for all but the most abundant proteins by incorporating a novel data interpretation method that allows accurate quantitation to occur. This additional separation is all achieved within a workflow with no discernible deleterious effect on throughput. Consequently, TWIMS greatly enhances proteome coverage and can be reliably used for quantification when using an alternative product ion quantification strategy. Using TWIMS in biomarker discovery in human plasma is thus recommended.

Identification of osteoarthritis biomarkers by proteomic analysis of synovial fluid

OBJECTIVE

To use proteomic analysis to identify novel candidate biomarker proteins in synovial fluid for the differential diagnosis of osteoarthritis and rheumatoid arthritis.

METHODS

Synovial fluid samples were analysed using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). Data were used to generate an artificial neural network (ANN). The identification of one protein peak was confirmed via Western blotting.

RESULTS

Fluid samples were analysed from 36 patients with osteoarthritis and 24 with rheumatoid arthritis. In total, three protein peaks (mass-to-charge ratio [m/z] 3893, 10,576 and 14,175 Da) were identified as potential biomarkers for osteoarthritis. The ANN differentiated between osteoarthritis and rheumatoid arthritis with a sensitivity of 89.4% and a specificity of 91.2%. The protein peak at m/z 10 576 was identified as S100 calcium binding protein A12 (S100A12).

CONCLUSIONS

A combination of SELDI-TOF-MS and ANN identified osteoarthritis biomarkers. SELDI-TOF-MS may be a useful tool in the screening of synovial fluid for osteoarthritis diagnosis.

Non invasive prenatal diagnosis of aneuploidy: next generation sequencing or fetal DNA enrichment?

Current invasive procedures [amniocentesis and chorionic villus sampling (CVS)] pose a risk to mother and fetus and such diagnostic procedures are available only to high risk pregnancies limiting aneuploidy detection rate. This review seeks to highlight the necessity of investing in non invasive prenatal diagnosis (NIPD) and how NIPD would improve patient safety and detection rate as well as allowing detection earlier in pregnancy. Non invasive prenatal diagnosis can take either a proteomics approach or nucleic acid-based approach; this review focuses on the latter. Since the discovery of cell free fetal DNA (cffDNA) and fetal RNA in maternal plasma, procedures have been developed for detection for monogenic traits and for some have become well established (e.g., RHD blood group status). However, NIPD of aneuploidies remains technically challenging. This review examines currently published literature evaluating techniques and approaches that have been suggested and developed for aneuploidy detection, highlighting their advantages and limitations and areas for further research.

Maternal serum protein profile and immune response protein subunits as markers for non-invasive prenatal diagnosis of trisomy 21, 18, and 13

OBJECTIVES

To use proteomics to identify and characterize proteins in maternal serum from patients at high-risk for fetal trisomy 21, trisomy 18, and trisomy 13 on the basis of ultrasound and maternal serum triple tests.

METHODS

We performed a comprehensive proteomic analysis on 23 trisomy cases and 85 normal cases during the early second trimester of pregnancy. Protein profiling along with conventional sodium dodecyl sulfate polyacrylamide gel electrophoresis/Tandem mass spectrometry analysis was carried out to characterize proteins associated with each trisomy condition and later validated using Western blot.

RESULTS

Protein profiling approach using surface enhanced laser desorption/ionization time-of-flight mass (SELDI-TOF/MS) spectrometry resulted in the identification of 37 unique hydrophobic proteomic features for three trisomy conditions. Using sodium dodecyl sulfate polyacrylamide gel electrophoresis followed by Matrix Assisted Laser Desorption Ionization - Time of Flight/Time of Flight (MALDI-TOF/TOF) and western blot, glyco proteins such as alpha-1-antitrypsin, apolipoprotein E, apolipoprotein H, and serum carrier protein transthyretin were identified as potential maternal serum markers for fetal trisomy condition. The identified proteins showed differential expression at the subunit level.

CONCLUSIONS

Maternal serum protein profiling using proteomics may allow non-invasive diagnostic testing for the most common trisomies and may complement ultrasound-based methods to more accurately determine pregnancies with fetal aneuploidies.