Most often overlooked on a standard blood test are the mean corpuscular volume (MCW) and Red Blood Cell Distribution Width (RDW). How do they change during aging, and what’s associated with all-cause mortality risk? Also, with the goal of optimizing MCV and RDW, how does my diet correlate with these biomarkers?
To make it easier to review the aging and all-cause mortality data for the circulating biomarkers that are contained within the biological age calculator, Phenotypic Age (see https://michaellustgarten.wordpress.com/2019/09/09/quantifying-biological-age/), here’s a checklist!
2. Creatinine: https://michaellustgarten.wordpress.com/2019/11/18/optimizing-biologic-age-creatinine/
3. Glucose: https://michaellustgarten.wordpress.com/2019/10/04/blood-glucose-whats-optimal/
4. C-reactive protein: https://michaellustgarten.wordpress.com/2019/10/19/optimizing-biological-age-crp/
5. Lymphocyte %: https://michaellustgarten.wordpress.com/2019/11/16/lympho-mortal/
6. Mean corpuscular volume (MCV): https://michaellustgarten.wordpress.com/2019/10/14/optimizing-biological-age-mcv/
7. Red cell distribution width (RDW%): https://michaellustgarten.wordpress.com/2019/09/25/optimizing-biological-age-rdw/
8. Alkaline phosphatase: https://michaellustgarten.wordpress.com/2019/10/07/alkaline-phosphatase/
9. White blood cells: https://michaellustgarten.wordpress.com/2019/10/11/blood-testing-whats-optimal-for-wbc-levels/
The coronary artery calcification (CAC) score is a measure of how much calcification is in the coronary arteries, and accordingly, is an in vivo measure of atherosclerosis. Why is the CAC score important? Besides its role in atherosclerosis, risk of death for all causes goes up at any age as the CAC score increases. For ex., in people younger than 50 (left side below), as the CAC score increases from 0 to 1-399, 400-999, and > 1000, risk of death for all causes increases by ~10-fold, from 2.3 per 1000 person years (PY) to 6.1/1000, 9.7/1000, and 22.7/1000. Similarly, for people older than 70y (right side below), as the CAC score increases, baseline all-cause mortality risk increases ~15-fold, from 5.6/1000 to 21.6/1000, 44.3/1000, and 76/1000, respectively (Hartaigh et al. 2016):
Are blood biomarkers associated with CAC? When the CAC score was elevated, a greater percentage of white blood cells (WBCs) that were neutrophils and the red blood cell distribution width (RDW%) were higher, whereas lower CAC scores were associated with higher levels for the fraction of lymphocytes divided by total WBCs and higher total red blood cells (den Harder et al. 2018):
In agreement with these data, CAC scores > 100 were associated with a higher RDW% (13.0%) and a higher neutrophil/lymphocyte ratio (NLR; 1.54), when compared with CAC < 100 (RDW = 12.8%; NLR = 1.39; Gürel et al. 2019).
The findings that a higher RDW% and higher levels of neutrophils, but lower levels of lymphocytes are associated with a higher CAC score is in agreement with the data for how these variables change with aging and their associations with all-cause mortality risk. First, note that I previously reported that RDW% increases during aging and is associated with an increased risk of death from all causes (https://michaellustgarten.wordpress.com/2019/09/25/optimizing-biological-age-rdw/). Similarly, neutrophils increase, whereas lymphocytes decrease, thereby leading to a higher neutrophil/lymphocyte ratio during aging, which is associated with an increased all-cause mortality risk (https://michaellustgarten.wordpress.com/2019/10/10/neutrophil-lymphocyte-ratio-and-survival/).
If you’re interested, please have a look at my book!
References
den Harder AM, de Jong PA, de Groot MCH, Wolterink JM, Budde RPJ, Iŝgum I, van Solinge WW, Ten Berg MJ, Lutgens E, Veldhuis WB, Haitjema S, Hoefer IE, Leiner T. Commonly available hematological biomarkers are associated with the extent of coronary calcifications. Atherosclerosis. 2018 Aug;275:166-173. doi: 10.1016/j.atherosclerosis.2018.06.017.
Gürel OM, Demircelik MB, Bilgic MA, Yilmaz H, Yilmaz OC, Cakmak M, Eryonucu B. Association between Red Blood Cell Distribution Width and Coronary Artery Calcification in Patients Undergoing 64-Multidetector Computed Tomography. Korean Circ J. 2015 Sep;45(5):372-7. doi: 10.4070/kcj.2015.45.5.372.
Hartaigh BÓ, Valenti V, Cho I, Schulman-Marcus J, Gransar H, Knapper J, Kelkar AA, Xie JX, Chang HJ, Shaw LJ, Callister TQ, Min JK. 15-Year prognostic utility of coronary artery calcium scoring for all-cause mortality in the elderly. Atherosclerosis. 2016 Mar;246:361-6. doi: 10.1016/j.atherosclerosis.2016.01.039.
Can biological age be optimized? The red blood cell (RBC) distribution width (RDW%) is one of the variables included in the PhenoAge biological age calculator (see https://michaellustgarten.wordpress.com/2019/09/09/quantifying-biological-age/). Although the RDW% reference range is 11.5% – 14.5%, what values are optimal in terms a youthful biological age, and minimized disease risk?
First, let’s define RDW%. RDW% is calculated by dividing the standard deviation of the average mean corpuscular volume (i.e. the average volume inside red blood cells, defined as MCV, upper right panel; image via Danese et al. 2015). When the volume inside red blood cells is approximately the same across all RBCs (upper left panel), the RDW% will be narrow, as shown by the dashed line in the upper right panel. Conversely, during aging and in many diseases, the size and volume of RBCs are altered, resulting in a more broad RDW% (bottom left and right panels):
In terms of RDW%, what’s optimal for health and longevity? In the the largest study (3,156,863 subjects) that investigated the association for risk of death for all causes with RDW%, maximally reduced risk of death was observed for RDW% between 11.4 – 12.5% (percentiles 1-5, 5-25), with mortality risk increasing for values < 11.3%, and > 12.6% (Tonelli et al. 2019):
This has been confirmed in other relatively large studies (240,477 subjects), as RDW% values < 12.5% were associated with maximally reduced all-cause mortality risk, with values > 12.5 associated with an increasing all-cause mortality risk (Pilling et al. 2018):
How does RDW% change during aging? For the 1,907 subjects of Lippi et al. (2014), RDW% increased during aging:
In support of this finding, RDW% also increased during aging in a larger study that included 8,089 subjects (Hoffmann et al. 2015).
Collectively, when considering the all-cause mortality and aging data, RDW% values ~ 12.5% may be optimal for health and longevity. What are my RDW% values? Plotted below are 18 RDW% measurements since 2015 (blue circles). First, note my average RDW% during that time (black line) is 12.8%, which isn’t far from the 12.5% that may be optimal for health and longevity. However, note the trend line (red), which indicates that my RDW% values are increasing during aging!
How do I plan on reducing my RDW%? A moderate strength correlation exists between my calorie intake with RDW% (r = 0.53), with a higher daily average calorie intake being associated with a higher RDW%:
My plan is to shoot for a daily calorie intake ~2600 over the next month, and then retest my RDW% (and the rest of the CBC). Hopefully that brings my RDW% down to 12.5% or less. If that doesn’t work, I’ll re-calibrate, and try something else!
If you’re interested, please have a look at my book!
References
Danese E, Lippi G, Montagnana M. Red blood cell distribution width and cardiovascular diseases. J Thorac Dis. 2015 Oct;7(10):E402-11. doi: 10.3978/j.issn.2072-1439.2015.10.04.
Hoffmann JJ, Nabbe KC, van den Broek NM. Red cell distribution width and mortality in older adults: a meta-analysis. Clin Chem Lab Med. 2015 Nov;53(12):2015-9. doi: 10.1515/cclm-2015-0155.
Lippi G, Salvagno GL, Guidi GC. Red blood cell distribution width is significantly associated with aging and gender. Clin Chem Lab Med. 2014 Sep;52(9):e197-9. doi: 10.1515/cclm-2014-0353.
Pilling LC, Atkins JL, Kuchel GA, Ferrucci L, Melzer D. Red cell distribution width and common disease onsets in 240,477 healthy volunteers followed for up to 9 years. PLoS One. 2018 Sep 13;13(9):e0203504. doi: 10.1371/journal.pone.0203504.
Tonelli M, Wiebe N, James MT, Naugler C, Manns BJ, Klarenbach SW, Hemmelgarn BR. Red cell distribution width associations with clinical outcomes: A population-based cohort study. PLoS One. 2019 Mar 13;14(3):e0212374. doi: 10.1371/journal.pone.0212374.
Michael Lustgarten 