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Meehan C, Lecocq S, Penner G (2024).PLoS ONE 19(8): e0307678.
Abstract:
An approach for the agnostic identification and validation of aptamers for the prediction of a medical state from plasma analysis is presented in application to a key risk factor for Alzheimer’s disease. brain amyloid deposition. This method involved the use of a newly designed aptamer library with sixteen random nucleotides interspersed with fixed sequences called a Neomer library. The Neomer library approach enables the direct application of the same starting library on multiple plasma samples, without the requirement for pre-enrichment associated with the traditional approach. Eight aptamers were identified as a result of the selection process and screened across 390 plasma samples by qPCR assay. Results were analysed using multiple machine learning algorithms from the Scikit-learn package along with clinical variables including cognitive status, age and sex to create predictive models. An Extra Trees Classifier model provided the highest predictive power. The Neomer approach resulted in a sensitivity of 0.88. specificity of 0.76. and AUC of 0.79. The only clinical variables that were included in the model were age and sex. We conclude that the Neomer approach represents a clear improvement for the agnostic identification of aptamers (Aptamarkers) that bind to unknown biomarkers of a medical state.
Gregory Penner, Soizic Lecocq, Anaëlle Chopin, Ximena Vedoya, Simone Lista, Andrea Vergallo, Francois-Xavier Lejeune & Harald Hampel (2019) Blood-based diagnostics of Alzheimer’s disease, Expert Review of Molecular Diagnostics, 19:7, 613-621,DOI: 10.1080/14737159.2019.1626719
Abstract:
This review is focused on the methods used for biomarker discovery for Alzheimer’s disease (AD) in blood rather than on the nature of the biomarkers themselves. All biomarker discovery programs explicitly rely on contrasts in phenotype as a basis for defining differences. In this review, we explore the basis of contrasting choices as a function of the type of biomarker (genetic, protein, metabolite, non-coding RNA, or pathogenic epitope). We also provide an overview of the capacity to identify pathogenic epitopes with our new platform called Aptamarkers. It is suggested that a pre-existing hypothesis regarding the pathophysiology of the disease can act as a constraint to the development of biomarkers. Limiting putative biomarkers to those that have postulated role in the pathophysiology of the disease imposes an unrealistic constraint on biomarker development. The understanding of Alzheimer’s disease would be accelerated by agnostic , non-hypothesis-based biomarker discovery methods. There is a need for more complex contacts and more complex mathematical models.
Gregory Penner, Soizic Lecocq, Anaëlle Chopin, Ximena Vedoya, Simone Lista, Andrea Vergallo, Francois-Xavier Lejeune & Harald Hampel (2019) Blood-based diagnostics of Alzheimer’s disease, Expert Review of Molecular Diagnostics, 19:7, 613-621,DOI: 10.1080/14737159.2019.1626719
Abstract:
This review is focused on the methods used for biomarker discovery for Alzheimer’s disease (AD) in blood rather than on the nature of the biomarkers themselves. All biomarker discovery programs explicitly rely on contrasts in phenotype as a basis for defining differences. In this review, we explore the basis of contrasting choices as a function of the type of biomarker (genetic, protein, metabolite, non-coding RNA, or pathogenic epitope). We also provide an overview of the capacity to identify pathogenic epitopes with our new platform called Aptamarkers. It is suggested that a pre-existing hypothesis regarding the pathophysiology of the disease can act as a constraint to the development of biomarkers. Limiting putative biomarkers to those that have postulated role in the pathophysiology of the disease imposes an unrealistic constraint on biomarker development. The understanding of Alzheimer’s disease would be accelerated by agnostic , non-hypothesis-based biomarker discovery methods. There is a need for more complex contacts and more complex mathematical models.
Gregory Penner, Soizic Lecocq, Anaëlle Chopin, Ximena Vedoya, Simone Lista, Andrea Vergallo, Francois-Xavier Lejeune & Harald Hampel (2019) Blood-based diagnostics of Alzheimer’s disease, Expert Review of Molecular Diagnostics, 19:7, 613-621,DOI: 10.1080/14737159.2019.1626719
Abstract:
This review is focused on the methods used for biomarker discovery for Alzheimer’s disease (AD) in blood rather than on the nature of the biomarkers themselves. All biomarker discovery programs explicitly rely on contrasts in phenotype as a basis for defining differences. In this review, we explore the basis of contrasting choices as a function of the type of biomarker (genetic, protein, metabolite, non-coding RNA, or pathogenic epitope). We also provide an overview of the capacity to identify pathogenic epitopes with our new platform called Aptamarkers. It is suggested that a pre-existing hypothesis regarding the pathophysiology of the disease can act as a constraint to the development of biomarkers. Limiting putative biomarkers to those that have postulated role in the pathophysiology of the disease imposes an unrealistic constraint on biomarker development. The understanding of Alzheimer’s disease would be accelerated by agnostic , non-hypothesis-based biomarker discovery methods. There is a need for more complex contacts and more complex mathematical models.
Lecocq S, Spinella K, Dubois B, Lista S, Hampel H, Penner G (2018) Aptamers as biomarkers for neurological disorders. Proof of concept in transgenic mice. PLoS ONE 13(1):e0190212.
Abstract:
The act of selecting aptamers against blood serum leads to deep libraries of oligonucleotide sequences that bind to a range of epitopes in blood. In this study we developed an enriched aptamer library by performing positive selection against a pool of blood serum samples from transgenic mice (P301S) carrying the human tau gene and counter selecting against pooled blood serum from negative segregant (wild type) mice. We demonstrated that a large proportion of the aptamer sequences observed with next generation sequence (NGS) analysis were the same from selection round 5 and selection round 6. As a second step, we applied aliquots of the selection round 5 enriched library to blood serum from 16 individual mice for a single round of selection. Each of these individual libraries were characterized through NGS analysis and the changes in relative frequency in aptamers from transgenic mice versus wild type were used to construct a diagnostic fingerprint of the effect of the action of the transgene on the composition of blood serum. This study serves as a model for similar applications with human subjects.
Lecocq S, Spinella K, Dubois B, Lista S, Hampel H, Penner G (2018) Aptamers as biomarkers for neurological disorders. Proof of concept in transgenic mice. PLoS ONE 13(1):e0190212.
Abstract:
The act of selecting aptamers against blood serum leads to deep libraries of oligonucleotide sequences that bind to a range of epitopes in blood. In this study we developed an enriched aptamer library by performing positive selection against a pool of blood serum samples from transgenic mice (P301S) carrying the human tau gene and counter selecting against pooled blood serum from negative segregant (wild type) mice. We demonstrated that a large proportion of the aptamer sequences observed with next generation sequence (NGS) analysis were the same from selection round 5 and selection round 6. As a second step, we applied aliquots of the selection round 5 enriched library to blood serum from 16 individual mice for a single round of selection. Each of these individual libraries were characterized through NGS analysis and the changes in relative frequency in aptamers from transgenic mice versus wild type were used to construct a diagnostic fingerprint of the effect of the action of the transgene on the composition of blood serum. This study serves as a model for similar applications with human subjects.