Tag Archives: MCV

Quantifying Biological Age: Blood Test #3 in 2022

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Join us on Patreon! https://www.patreon.com/MichaelLustgartenPhD

Levine’s Biological age calculator is embedded as an Excel file in this link from my website: https://michaellustgarten.com/2019/09/09/quantifying-biological-age/

An epigenetic biomarker of aging for lifespan and healthspan https://pubmed.ncbi.nlm.nih.gov/29676998/

Underlying features of epigenetic aging clocks in vivo and in vitro https://pubmed.ncbi.nlm.nih.gov/32930491/

Population Specific Biomarkers of Human Aging: A Big Data Study Using South Korean, Canadian, and Eastern European Patient Populations https://pubmed.ncbi.nlm.nih.gov/29340580/

Methionine Restriction Extends Lifespan-What’s Optimal For Protein Intake? n=1 Analysis

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Join us on Patreon! https://www.patreon.com/MichaelLustgartenPhD

Papers referenced in the video:

Life-Span Extension in Mice by Preweaning Food Restriction and by Methionine Restriction in Middle Age https://pubmed.ncbi.nlm.nih.gov/19414512/

Low methionine ingestion by rats extends life span https://pubmed.ncbi.nlm.nih.gov/8429371/

Fasting glucose level and all-cause or cause-specific mortality in Korean adults: a nationwide cohort study https://pubmed.ncbi.nlm.nih.gov/32623847/

Total plasma homocysteine and cardiovascular risk profile. The Hordaland Homocysteine Study https://pubmed.ncbi.nlm.nih.gov/7474221/

Predicting Age by Mining Electronic Medical Records with Deep Learning Characterizes Differences between Chronological and Physiological Age https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5716867/

Association between low-density lipoprotein cholesterol and cardiovascular mortality in statin non-users: a prospective cohort study in 14.9 million Korean adults https://pubmed.ncbi.nlm.nih.gov/35218344/

Blood counts in adult and elderly individuals: defining the norms over eight decades of life https://pubmed.ncbi.nlm.nih.gov/32030733/

Blood Testing: MCV, RDW. What’s Optimal for Health and Longevity?

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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?

Quantifying Biological Age: Checklist

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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!

1. Albumin: https://michaellustgarten.wordpress.com/2019/09/22/optimizing-serum-levels-of-albumin-data-from-20-blood-tests/

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/

 

Optimizing Biological Age: MCV

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Mean corpuscular volume (MCV) is one of the 10 variables included in the biological age calculator, PhenoAge (see https://michaellustgarten.wordpress.com/2019/09/09/quantifying-biological-age/). It’s calculated by dividing the fraction of the blood that contains RBCs (hematocrit) by RBCs (MCV = hematocrit/RBC), thereby identifying the average volume contained within red blood cells. Although the MCV reference range is 80 – 100 femtoliters (10^-15L), what’s optimal in terms of a youthful biological age, and minimized disease risk?

MCV increases during aging. In support of this, using a small subset of samples from the Baltimore Longitudinal Study on Aging (values not in parentheses), MCV increased from average values of 88.8 in young (18-39y), to 91.3 in middle-aged (40-59y), to 92.4 in old (>60y) subjects. Similarly, MCV also increased in the full sample size from the Baltimore Longitudinal Study on Aging (values in parentheses) from 89.2 to 91.1 to 92.9 in young, middle-aged and old, respectively (Araki and Rifkind, 1984):

Screen Shot 2019-10-12 at 3.32.31 PM

In a larger study that included 3,358 subjects, MCV increased from median values of 92.2 in women and 93.4 in men younger than 60y to 94.2 and 95.7 in women and men older than 60y, respectively (Lee et al. 2018):

mcv age

When considering that MCV increases during aging, one would predict that higher levels would be associated with an increased risk of death of all causes. In support of this, in the 36,260 subjects of Yoon et al. (2016), MCV levels > 94.2 in women and > 95.8 in men (Tertile 4) were associated with a 55% and 44% increased risk of death from all causes, respectively, when compared with MCV values between 89.2 – 91.6 in women and 90.5 – 93 in men (Tertile 2):

mcv acm

Collectively, these data suggest that a lower MCV may be better in terms of biologic youth,  and for a lower risk of death from all causes. What are my MCV values? I’ve measured MCV 25 times over the past 16 years. In my 30’s, I measured it 7 times, with an average MCV = 90. In my 40’s, I’ve measured it 18 times, for an average value = 91.1. Although these 2 groups of data are not significantly different (p=0.09), the red trendline for these data is slightly up (R2=0.02), which suggests that my MCV is slowly increasing with age:

mcv me

Although my MCV values are seemingly far from the increased mortality risk of Yoon et al. (> 95.8), it increases during aging, so I’ve definitely got my eye on it. Should it start to increase, I’ll intervene with dietary changes. Stay tuned!

 

If you’re interested, please have a look at my book!

 

References

Araki K, Rifkind JM. Age dependent changes in osmotic hemolysis of human erythrocytes. J Gerontol. 1980 Jul;35(4):499-505.

Lee Eun-jin, Kim Mi-young, Lee Eun-yeop, Jeon Beom, Lee Ji-won, Kim Han-sung, Kang Hee-jeong, Lee Young-kyung, Eun Jin Lee, Miyoung Kim, Eunyup Lee, Kibum Jeon, Jiwon Lee, Han-Sung Kim, Hee Jung Kang, Young Kyung Lee.vEstablishment of reference section for general blood test in healthy elderly. Establishing Reference Intervals for Complete Blood Cell Count in Healthy Korean Elderly Individuals. J Lab Med Qual Assur 2018; 40: 27-37. doi.org/10.15263/jlmqa.2018.40.1.27.

Yoon HJ, Kim K, Nam YS, Yun JM, Park M. Mean corpuscular volume levels and all-cause and liver cancer mortality. Clin Chem Lab Med. 2016 Jul 1;54(7):1247-57. doi: 10.1515/cclm-2015-0786.