D- and L-amino acid regression for glomerular filtration rate estimation
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Solution Overview
Problem
Current methods for estimating kidney function, such as using creatinine and cystatin C, are not sensitive enough to accurately measure glomerular filtration rate across a wide range of kidney function stages without burdening patients or practitioners, and existing markers do not correlate well with the gold standard of inulin clearance.
Innovation Solution
A method and system that utilize D- and L-amino acid levels in blood samples, analyzed through regression analysis, to estimate kidney function by calculating a value (Y) that correlates better with glomerular filtration rate than conventional markers, allowing for more accurate estimation of kidney function across various stages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If inulin clearance is used to measure glomerular filtration rate, then measurement accuracy is improved, but patient burden and operational complexity increase significantly
Solution Approach 1:
The patent extracts the essential measurement function from the complex inulin clearance procedure by identifying and measuring specific amino acid metabolites (D-amino acids and L-amino acids) that directly reflect glomerular filtration status. This extraction allows estimation of GFR using simple blood amino acid level measurements rather than the complex multi-step inulin clearance protocol
Solution Approach 2:
The patent introduces amino acid metabolites as intermediary markers that mediate between the gold standard inulin clearance measurement and clinically usable parameters. These amino acid levels serve as intermediate indicators that correlate with GFR and can be measured easily, bridging the gap between accurate but complex measurement and simple but inaccurate markers
2Ease of operation
If creatinine is used as a kidney function marker, then ease of measurement is improved, but measurement sensitivity and accuracy worsen
Solution Approach 1:
The patent changes the measurement parameter from creatinine levels to amino acid metabolite levels (specifically D-amino acids and L-amino acids). This parameter change maintains the simplicity of blood-based measurement while significantly improving the correlation with actual glomerular filtration rate, as amino acid levels respond more sensitively to changes in kidney function
3Measurement precision
If cystatin C is used as a GFR marker, then measurement sensitivity in early kidney disease is improved, but accuracy in end-stage kidney disease deteriorates
Solution Approach 1:
The patent employs amino acid metabolites as a universal marker that functions effectively across the entire spectrum of kidney disease severity. Unlike cystatin C which fails at end-stage, the amino acid levels maintain their correlation with GFR from early to late stages, providing a multi-functional marker that works universally throughout disease progression
4Productivity
If conventional kidney function markers are used, then clinical workflow simplicity is maintained, but diagnostic accuracy across all kidney disease stages deteriorates
Solution Approach 1:
The patent enables the measurement system to self-serve by using routine blood amino acid level measurements that can be obtained through standard laboratory procedures already present in most clinical settings. This self-service approach maintains workflow efficiency while improving accuracy, as the same blood draw used for routine chemistry can now provide amino acid levels for GFR estimation
Data Source
AI summary
The present invention provides a method comprising a step of estimating the kidney function of an arbitrary subject by a regression analysis which employs the amount of a D, L-amino acid in a biological sample from the arbitrary subject as an explanatory variable and employs the amount of filtrated glomeruli in the arbitrary subject as an object variable, by employing a previously determined formula (I): Y=a1·X1+a2·X2+ . . . +an·Xn+b (I) [wherein a1 to an independently represent a constant obtained by the regression analysis; X1 to Xn independently represent a variable of the amount of the D,L-amino acid which is selected by the regression analysis; and b represents a constant obtained by the regression analysis] on the basis of the Y value calculated from the amount of the D, L-amino acid in the biological sample from the object to be evaluated. Also provided is a system for carrying out the method.