Early Stage Detection for Alzheimers and other Autoimmune Diseases

Abstract

The present invention describes a non-invasive system and method for detecting early stage Alzheimer's and other autoimmune diseases associated with neurological deficits, including Multiple Sclerosis and Parkinson's Disease. By analyzing the volatile organic compounds (VOCs) found in the otic canal either in gaseous form or as what is commonly known as “earwax”, the current invention discloses how these disease signatures/profiles are illustrative of the presence or absence of a particular disease.

Claims

1. A method for assessing for a disease or condition, said method comprising: i) collecting a sample from the otic canal; ii) analyzing content of at least one VOC in said sample; iii) forming a signature indicative of said analyzed content; iv) comparing said signature to a library of signatures associated with a disease or condition; and v) acknowledging similarities between said signature formed in iii) and one or a plurality of library signatures.

2. The method of claim 1 wherein said sample comprises a gaseous sample.

3. The method of claim 1 wherein said sample comprises a coating on the wall of the otic canal.

4. The method of claim 1 wherein said sample comprises earwax.

5. The method of claim 2 wherein analyzing said gaseous sample comprises: inserting a probe into said otic canal; contacting a sensing surface of said probe with otic canal gas; collecting data resulting from said contacting; forming a signature by analyzing said data resulting from said contacting; comparing said signature to a library of signatures associated with a disease or condition; and acknowledging similarities between said signature formed by analyzing said data resulting from said contacting and one or a plurality of library signatures.

6. The method of claim 2 wherein collecting a sample from the otic canal comprises: inserting a probe into said otic canal; and drawing gas from said otic canal into said probe.

7. The method of claim 6 wherein said collecting a sample from the otic canal comprises: causing said gas to flow from said probe into a device that analyzes VOCS.

8. The method of claim 7 wherein said device that analyzes VOCs comprises a nanosensing element.

9. The method of claim 6, wherein said collecting a sample from the otic canal comprises: causing said gas to flow into a cartridge; sealing said cartridge; and delivering said sealed cartridge for said analyzing.

10. The method of claim 3 wherein said collecting a sample from the otic canal comprises physically removing said coating using a solid support.

11. The method of claim 10 wherein said solid support is selected from the group consisting of: an earwax removal tool and a swab.

12. The method of claim 10 further comprising inserting said solid support into a chamber configured to deliver said sample for said analyzing.

13. The method of claim 12 further comprising thermally exciting said sample on said solid support to promote movement of VOCs and subsequent contact of at least one VOC with at least one sensing element.

14. The method of claim 10 further comprising solvent extracting said coating from said solid support.

15. The method of claim 14 further comprising thermally exciting said extracted sample to promote movement of VOCs and subsequent contact of at least one voe with at least one sensing element.

16. The method of claim 3 wherein said collecting a sample from the otic canal comprises extracting with a liquid solvent.

17. The method of claim 16 further comprising thermally exciting said extracted sample to promote movement of VOCs and subsequent contact of at least one VOC with at least one sensing element.

18. The method of claim 2 wherein analyzing said gaseous sample is performed by contacting at least one nanosensing element with gas in the otic canal.

19. A method for forming a library of signatures associated with a first disease or condition, said method comprising: i) assembling a cohort of informed subjects; ii) associating each member of said cohort with any or all diseases said each member has been diagnosed to have; iii) collecting a sample from the otic canal of each member; iv) analyzing content of at least one VOC in said sample; v) forming a signature indicative of said analyzed content; vi) identifying as a control member for said first disease or condition, a subject not associated with said first disease or condition; vii) comparing a plurality of control members' VOC content for said first disease or condition with VOC content of each member diagnosed to have said first disease or condition; viii) documenting differences in analyzed VOC content between control members and diagnosed members to form a signature associated with said first disease or condition.

20. The method according to claim 19 further comprising: forming a library of signatures associated with a second disease or condition by applying vi), vii), and viii) to said second disease or condition.

21. The method according to claim 20 further comprising: repeating the method of claim 20 to a plurality of second diseases or conditions; compiling said libraries of signatures in a collection comprising a plurality of signatures associated with a plurality of diseases or conditions.

Description

EXAMPLES

[0025] A panel of patients is chosen. Informed consent is obtained. Patients are associated with one or more disease(s). When patients have agreed, both tool or swab derived samples (earwax) and otic canal gasses are collected. Samples are analyzed and a signature pattern output is obtained. It is not essential to identify any specific VOC, the sensing pattern obtained by passing the sample over the block provides sufficient distinguishing data even when the chemical structure of the VOC is unknown. Patients with a particular diagnosis are associated with that disease. Patients without that diagnosis (but possibly, and most likely, with a diagnosis for one or more other disease(s) can serve as control for each disease in the panel of patients.

[0026] When gas is targeted for analysis, a gas sample outside the otic canal may be analyzed as a control factor. The sensor device used for obtaining and analyzing otic gas may be activated outside the canal to collect control samples. For example, a sample of gas from the auricular area, the external meatus, etc., may serve to control for ambient gases the subject may be immersed in.

[0027] The data are fed into a processor either in the collection device itself or an associated component which applies artificial intelligence or machine learning to identify portions of each patient's signature may be associated with a particular diagnosis. In some circumstances a part of the signature, e.g., a ratio of VOC A to VOC B may be similar between a plurality of diseases. But other parts of the signature may differentiate between the diseases. A library of signature patterns is thus collected with characteristic signature elements being associated with a disease as signature for that disease. Earwax and otic canal gasses are separately analyzed but may be correlated or cross-referenced. Left- and right-side readings are cross-referenced and correlated when possible. Differences may be indicative of disease differences between hemispheres, circulatory aberrations, previous injury, sleep positions, headset wearing, etc. Data may show that left-right differences can provide information suggesting lesion location, or may suggest preferences for using the right or left ear for testing depending on the subject's behaviors, habits, and activities.

[0028] A second group of patients is similarly evaluated to confirm or adjust disease signatures. The system is then used for diagnosing patients. In preferred practice, over a period of years, the data are periodically reevaluated and refined. For example, patients who are diagnosed with a disease months or years after the initial signature development may have their data reevaluated for potential indication of a pre-disease state or early disease detection. Having a signature library available, a patient comes to clinic and as a part of screening has an otoscope like device inserted in the ear canal. This exemplary device actually includes an otoscope function incorporating a light and a view-port. The medical provider uses the optics of the otoscope to center the device within the canal. A gas sample is drawn into and analyzed in the otoscope device. The device communicates the patient's otic gas signature electronically to a home device which displays and/or prints out a report. A clinician then counsels the patient with emphases on current and developing disease(s) that are indicated or suggested through the device's comparison of the patient's VOC signature to the signature library for diseases.

[0029] An alternative embodiment format draws otic canal gases through the canal inserted portion of the device into an accessory device containing one or more sensing blocks. The gas replacing the gas removed by the device may be ambient air or a selected gas or mixture of gases. For example, an inert gas (which may or may not be a noble gas) in provided at a temperature or range of temperatures to optimize testing protocols, e.g., for speed, patient comfort, quality of results.

[0030] As the gases are drawn through the accessory device the depth of the otic probe may be adjusted. A low-volume transit tube, e.g., short with small inner diameter, allows obtention of results at a quicker pace and decreases temperature effects from gases flowing into the ear canal when these flows are not otherwise controlled. To the extent that colder air may be annoying to the subject, a heating coil or feeding line may reduce the irritative cold sensation. Slightly warming the air may also be advantageous for subliming or evaporating additional VOCs. Humidity may also be a controlled testing parameter. Polar vapors, water or otherwise, may encourage release or VOCs from the otic coating. Volunteer subjects or patients of different sizes, genders, races, and cultures are tested using probes with flowing gas.

[0031] The art mentioned above employed different means for assaying volatile compounds. The different means would be expected to have different sensitivities to different VOCs. In this current example, temperature is a variable that can change the signature profile. Accordingly, a VOC pattern associated with a disease, e.g., Alzheimer's Disease obtained, for example through GC-MS, cannot be assumed to be the same pattern when assayed with another sensor format. Thus, signatures should be clearly identified with the process under which they were obtained.

[0032] Nano FETs and other nano-sensor formats generally operate by changing electrical properties as a substance comes in close proximity to the sensor. The interaction between electrons of the sensed molecule and the sensor surface perturbs the steady state of that surface to elicit its signal. The altered distribution of electrons induced by a proximal molecule, (depending on the design of the nano-sensor) changes one or more electrical properties, e.g., impedance, resistance-conductivity, capacitance, inductance, etc. and thus the physical movement of a detectable particle, e.g., an electron, a photon, etc.

[0033] Specificity of coordination (interaction) between sensor surface and VOC molecule may be provided by functionalizing or decorating the carbon gate electrode. For example, many sequences of nucleic acid such as DNA or RNA will stringently coordinate or bind with the SWNT structure. These nucleic acids may be naturally occurring or synthetic. The ringed structures of the nucleic acids or other molecules such as peptides containing a large fraction of ringed structures associate strongly with the nanotubular structures. These functionalizing, or decorating, additions to the SWNTs serve to selectively capture proximal molecules. When the chemical geometry is changed, the gating characteristic of the associated carbon bridging the input and output electrodes is modulated. Differently decorated or heated elements respond differently different proximal VOC. A single element may be associated with a single sequence or a plurality of functionalizing sequences. Output characteristics of gating in response to one or more gaseous compounds, e.g., VOCs are then collated into a data library. When that NSE responds in the same manner, presence of the VOC is confirmed. Stringent selection of element functionalizations, and subsequent application of the controllable assay variables can optimize certainty of VOC identification at a desired level, for example, increasing manipulation of the variable parameters can achieve certainty of 99+%. In special circumstances, for example to develop rapid profiling of a new VOC signature (i.e., pathogen), a simplified screening protocol or developmental process may begin with a lower level of certainty, e.g., 85%, 95%, etc. Subsequent refinements then could be applied to raise the level of certainty until reaching a mathematical and chemical sensitivity to an acceptable level, e.g., a 99+% certainty while also minimizing false positives.

[0034] A single element may be capable of indicating the presence of more than one compound. For example, similar compounds may not be distinguished in their association/coordination with the element surface and therefore may in certain circumstances produce indistinguishable signals on their own. But the single element may, for example, in conjunction with one or more other elements provide definitive results with respect to the VOCs that may interact with any one element. Alternatively, the single element when operated at a different temperature, voltage or other variable may distinguish between the different compounds binding the element under static conditions. The discussion above describing the variable inputs and input patterns and different resulting outputs relates to such differentiation capabilities.

[0035] Since the manner through which a signature is obtained is determinative of the signature outcome a different assay technique thus requires validation processes to form and confirm VOC signatures for each disease of interest. While animal models may be illustrative, human data are preferred for better relevance to human diseases.