the hematocrit effect in dried micro sampling...different strategies for coping with the hematocrit...

Different strategies for copingDifferent strategies for coping with the hematocrit effect in dried

blood micro‐sampling

Sara Capiau, Pieter M.M. De Kesel and Christophe P. StoveChristophe Stove@UGent [email protected]

What can be analyzed with DBS?

(Almost) everything:

DNA/mRNAproteins

(trace) elements(trace) elementssmall molecules

General pros and cons of DBS sampling

• Ease of sampling/home sampling • Correct sampling• Minimally invasive• Small blood volumes

• Contamination risk• Sensitive analysis required

• Representative matrix (blood)• Stabilizing effect

• Extensive validation required‐ Site of punchingg

• Reduced biohazard • Convenient & cost‐effective

‐ Blood volume spotted‐ Hematocrit effectConvenient & cost effective

transport and storage• Straightforward sample

• Correlation between venous and capillary blood levels

Straightforward sample processing and analysis

• AutomatableAutomatable• # Animals ↓

De Kesel et al., Bioanalysis, 2013

General pros and cons of DBS sampling

• Ease of sampling/home sampling • Correct sampling• Minimally invasive• Small blood volumes

• Contamination risk• Sensitive analysis required

• Representative matrix (blood)• Stabilizing effect

• Extensive validation required‐ Site of punchingg

• Reduced biohazard • Convenient & cost‐effective

‐ Blood volume spotted‐ Hematocrit effectConvenient & cost effective

transport and storage• Straightforward sample

• Correlation between venous and capillary blood levels

Straightforward sample processing and analysis

• AutomatableAutomatable• # Animals ↓

De Kesel et al., Bioanalysis, 2014

The Hct effect in practice

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Source:

The Hct effect: a two‐fold problem

The impact of blood hematocrit can be divided into two aspects:

ANALYTICAL IMPACT

• Viscosity of the blood (differential spreading of blood with high and low Hct)low Hct)

• Extraction efficiency of the compounds (i.e. recovery)

• Matrix effects

PHYSIOLOGICAL IMPACT

• Blood‐to‐plasma ratio of compounds( f i bl d l [ ])(cfr. comparison blood‐plasma [ ])

*Hemato‐critical issues in quantitative analysis of dried blood spot: challenges and solutions. De Kesel et al. Bioanalysis, 2014

Whole DBS analysis

Pre‐cut Dried Blood SpotsPre cut Dried Blood SpotsYouhnovski et al., Rapid Comm. Mass Spectrom., 2011

f d d l dPerforated Dried Blood SpotsLi et al., Bioanalysis, 2011

Dried Matrix On Paper DisksMeesters et al., Bioanalysis, 2012

All require volumetric application of DBS!

DBS: Direct application vs. volumetric application

Volumetric application Non‐volumetric applicationVolumetric application Non‐volumetric application

vs.

Lab or Hospital Sampling @ home

Partial punch analysis Whole DBS analysis

Lab or Hospital Sampling @ home

Microfluidic‐based volumetric sampling (1)


http://dbs‐system.ch/technology/


G. Lenk, Karolinska Inst, SWEDEN


HemaPENTM (Trajan Scientific and Medical)

Volumetric Absorptive Microsampling

VAMS (Mitra®,VAMS (Mitra , Phenomenex) Volumetric sampling (10.2 ul), irrespective of hematocrit


Study Set‐up:

U l f EDTA i l d bl d• Use left‐over EDTA‐anticoagulated bloodfrom patients ( hospital departments)

• Compare liquid blood – VAMS – DBS

• Analytes: caffeine & paraxanthine

De Kesel et al., Analytica Chimica Acta, 2015


4550 [Caffeine]

2530354045

510152025

e (%

)

15‐10‐505

ffere

nce

35‐30‐25‐20‐15

Dif

‐50‐45‐40‐35

0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.550.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55

Hematocrit0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55



4550 [Caffeine]

2530354045

510152025

e (%

)

15‐10‐505

ffere

nce

35‐30‐25‐20‐15

Dif

‐50‐45‐40‐35

0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.550.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55

Hematocrit0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55


Volumetric Absorptive MicrosamplingEvaluation of impact of hematocrit on recovery:

• VAMS: Similar extraction procedure as for DBSp

• recovery at higher hematocrits

The calibration line had been set up at a relative high Ht; because of the impact of the Ht recovery of the vast majority because of the impact of the Ht, recovery of the vast majority

of the samples will be slightly higher than that of the calib.’sDe Kesel et al., Analytica Chimica Acta, 2015


Evaluation of impact of hematocrit on recovery:

→ extraction at 60 °C

Hct Caffeine Paraxanthine

Low QC High QC Low QC High QCLow QC High QC Low QC High QC

0.21 101.21 ± 3.40 98.45 ± 1.37 102.39 ± 2.76 98.26 ± 1.56

Absolute recovery

(mean ± SD, %)

0.42 101.46 ± 0.70 100.14 ± 2.76 99.20 ± 2.60 102.84 ± 1.66

0.48 106.77 ± 3.11 100.51 ± 2.64 100.62 ± 0.90 103.35 ± 1.58(mean SD, %) 0.48 106.77 3.11 100.51 2.64 100.62 0.90 103.35 1.58

0.62 104.68 ± 3.77 100.70 ± 2.05 103.80 ± 5.66 97.85 ± 4.31

The Hct effect: a two‐fold problem

The impact of blood hematocrit can be divided into two aspects:

ANALYTICAL IMPACT

• Viscosity of the blood (differential spreading of blood with high and low Hct)low Hct)

• Extraction efficiency of the compounds (i.e. recovery)

• Matrix effects

PHYSIOLOGICAL IMPACT Also to be

• Blood‐to‐plasma ratio of compounds( f i bl d l [ ])

Also to beevaluated in volumetric

(cfr. comparison blood‐plasma [ ]) DBS applications

Hct effect on extraction recovery

New materials

Qyntest® (Qynion):

Non cellulose multilayered material that would allow even spreading ofNon‐cellulose multilayered material that would allow even spreading of blood, irrespective of hematocrit

Mengerink et al, Bioanalysis, 2015

New Formats

HemaspotTM (Spot‐On‐Sciences) :

Minimizing the Hct effect

Prepare calibrators in blood with an appropriate Hct

s, 2013

., Bioanalysi

Capiau

et a

l.Sado

nes & C

De Kesel, S

=> Define target population

The hematocrit issue: a chicken‐and‐egg‐situation

Perform DBS analysis in a validated Hct interval

11;

u et al., 201

3

Only samples

oanalysis, 201

nes & Capiau

within this Hctrange yield valid

l

gels et al., Bio

Kesel, Sado

n results

Ing

De

However, how does one know ifthe Hct of a given DBS lies withinthi i t l?this interval?

Need for Hct prediction Need for Hct prediction

Estimating the Hct of DBS: K+

• [K+] intracellularly >> [K+] plasma and > 99% of cells are RBCs[K+] ti htl t ll d l i t i di id l i bilit• [K+] are tightly controlled no large interindividual variability

• K+ is universal• K+ proved to be stable in DBSK proved to be stable in DBS• K+ easily measurable in DBS


Bring a 3‐mm DBS punch in a small tube

Extract 2X with 50 µl 2.5 mM KCl in ultrapure H2Op 2

Measure [K+] in 90 µl via indirect potentiometry using the ISE (Ion Selective Electrode) module of theSelective Electrode) module of the Cobas 8000 Clinical Chemistry

Analyzer

Estimating the Hct of DBS: Application

K+‐based algorithm to correct for Hct effect

healthy volunteers (n = 61)&&

hospital patients (n = 117)

venous whole blood venous DBS

To determine[caffeine] [caffeine] To determineHct‐effect

T di t

[caffeine][paraxanthine]

[caffeine][paraxanthine]

To predictHct

[K+]

K+‐based algorithm to correct for Hct effect[caffeine] > LLOQ

n = 100 Hct range 0 18 – 0 47 Hct range 0.18 0.47

Reference set (n = 50)

• [Caffeine]DBS – [Caffeine]Blood303540

Corrected [DBS]

DEDUCE NEW CORRECTION ALGORITHM:051015202530

nce (%

)

Corrected [DBS]=

[DBS]*((‐0.4141*[K+]) + 1.5052) ‐30‐25‐20‐15‐10‐50

Differen

‐40‐35‐30

0.4 0.6 0.8 1.0 1.2 1.4 1.6[K+]



Test set (n = 50)


Corrected [DBS]

APPLY NEW CORRECTION ALGORITHM:

051015202530

nce (%

)

[ ]=

[DBS]*((‐0.4141*[K+]) + 1.5052) ‐30‐25‐20‐15‐10‐50

Differen

‐40‐35‐30

0.4 0.6 0.8 1.0 1.2 1.4 1.6[K+]



Test set (n = 50)


303540

• [Caffeine]corrected – [Caffeine]Blood

051015202530

nce (%

)

051015202530

nce (%

)

‐30‐25‐20‐15‐10‐50

Differen

‐30‐25‐20‐15‐10‐50

Differen

‐40‐35‐30

0.4 0.6 0.8 1.0 1.2 1.4 1.6[K+]

‐40‐35‐30

0.4 0.6 0.8 1.0 1.2 1.4 1.6[K+]

K+‐based algorithm to correct for Hct effect[paraxanthine] > LLOQ


Test set (n = 103)

303540 • [PRX]DBS – [PRX]Blood

Corrected [DBS]

APPLY NEW CORRECTION ALGORITHM:

051015202530

nce (%

)

Corrected [DBS]=

[DBS]*((‐0.4141*[K+]) + 1.5052) ‐30‐25‐20‐15‐10‐50

Differen

‐40‐35‐30

0.4 0.6 0.8 1.0 1.2 1.4 1.6[K+]

K+‐based algorithm to correct for Hct effect[paraxanthine] > LLOQ


Test set (n = 103)

303540 • [PRX]DBS – [PRX]Blood

303540

• [PRX]corrected – [PRX]Blood

051015202530

nce (%

)

051015202530

nce (%

)

‐30‐25‐20‐15‐10‐50

Differen

‐30‐25‐20‐15‐10‐50

Differen

‐40‐35‐30

0.4 0.6 0.8 1.0 1.2 1.4 1.6[K+]

‐40‐35‐30

0.4 0.6 0.8 1.0 1.2 1.4 1.6[K+]


• Straightforward sample prep • Requires sample prep• Straightforward sample prep.• Routine analyzer• Cheap

• Requires sample prep.• Destructive• Time consuming• Cheap

• Stable3 h

• Time‐consuming

• 3‐mm punch

• Adopted by other groups

Estimating the Hct of DBS: Hemoglobin

Optimization of extraction solventOptimization of extraction solvent

3h‐old DBS

3d‐old DBS Cobas 8000

Hb is apparently not stableStability of Hb in DBS vs. time

b(%

)

Total [Hb] vs. time

L)

Hb is apparently not stable

onof to

talH

b

MetHb↑

HbO ↓ al [H

b] (g

/dCo‐oximeter

Time (days)

Fractio HbO2 ↓

Tota

Time (days) Time (days)


• Additional Hb derivatives formed upon drying!

• Different Hb derivatives not all detected using routine measurements

HYPOTHESIS: Sum HbO2, metHb and HC = constant = measure for Hct?

*Age estimation of blood stains by hemoglobin derivative determination using reflectance spectroscopy. Bremmer et al. Forensic Sci Int. 2011


• Bremmer et al.:

Method that estimates the age of bloodspatters on crime scenes using the relative abundance of these Hb‐derivativesg

Non‐contact diffuse reflectance spectroscopy

Could we use this technique to measure the different Hb derivatives in DBS (and hence the Hb sum)?

YES! => non‐contact Hct estimation before DBS analysis


Method completely validated (Hct estimation independent of age DBS!)

i l ( 288)EDTA patient samples (n = 288)• Whole blood: ‘true’ Hct using Sysmex XE‐5000• Venous DBS: calculated HCT using non‐contact method

=> 234 out of 288 samples within 15% of true Hct> 234 out of 288 samples within 15% of true Hct=> 270 out of 288 samples within 20% of true Hct


Use of Hct prediction for Hct correction• Caffeine reference set: correlation between estimated Hct andCaffeine reference set: correlation between estimated Hct and

extent of Hct effect• Set up of Hct correction algorithmp g• Application to test set

30%

40%

and DBS

Caffeine test set (n = 48)

0%

10%

20%

en who

le blood

a

‐20%

‐10%

0%0.100 0.200 0.300 0.400 0.500 0.600

fferen

ce betwee

‐40%

‐30%% dif

Estimated Hct


Hemoglobin‐based hematocrit prediction: Non‐destructiveNon destructive No punching No sample prep No sample prep. Very fast Does not interrupt workflow drastically Does not interrupt workflow drastically Cheap Hi hl d ibl Highly reproducible Applicable for hematocrit correction

MERE SCANNING SUFFICES TO KNOW THE HCT OF A DBS!

Dried Plasma Spots

Dried Plasma Spots

2015

nalysis,,

rm, B

ioa

Stur

Dried Plasma Spots

Dried Plasma Spots

Hemaspot SETM (Spot‐On‐Sciences):

Conclusion

Thank You!

the hematocrit effect in dried micro sampling...different strategies for coping with the hematocrit...

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