Category Archives: Alkaline Phosphatase

Quantifying Biological Age: Blood Test #2 in 2022

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Biological Age Test #4 in 2020: Getting Better or Getting Worse?

My latest blood test results are in-how’s my biological age? In the video I discuss my dietary approach prior to my latest blood test, the blood test results, and my plan to improve them going forward.

Quantifying Biological Age: Blood Test Measurement #3 in 2020

In this video, I discuss data for 6 blood test measurements since 2018 that show a Phenotypic (Biological) Age that is ~14 years than my current age (47y).
 

15+ Years Younger Than My Chronological Age: Blood Test #2 In 2020

Exactly 1 month ago, my first biological age measurement of 2020 was 32.75y (https://michaellustgarten.wordpress.com/2020/02/14/biological-age-32-75y-chronological-age-47y-first-2020-measurement/). When considering that my chronological age is 47y, that’s a 14 year improvement, but I wasn’t (and still aren’t) satisfied. When I sent my blood for analysis, I was battling a mild upper respiratory infection (cough, no fever), which likely raised my WBCs, thereby resulting in a higher biologic age. Also, I was experimenting with a higher intake of meat, eggs, and cheese, to see what affect that it would have on my circulating biomarkers. On that blood test in February, my creatinine levels were higher than my 2015-2020 average value, and if those foods were associated with circulating levels of creatinine, reducing them should also reduce creatinine, and accordingly, further improve my biological age. I also assumed that all other variables on Levine’s Phenotypic Age calculator would be unchanged.

On March 9 2020, I sent my blood for analysis so that I could calculate biological age with Levine’s PhenotypicAge. Almost exactly as expected, my WBCs (4.7 * 10^3 cells/microliter) were closer to my 2015-2020 average value (4.6), rather than the higher value (5.8) in my blood test last month. Similarly, reducing my intake of beef, eggs, and cheese brought creatinine from 1.08 to 0.97 mg/dL, which is closer to its 5-year average (0.94 mg/dL). As a result, I further reduced my biological age by 1.14 years to 31.61y, which is 15+ years younger than my chronological!

pa 3.9.2020

Because I track my diet every day, I can investigate the correlation between my meat, eggs, and cheese intake with creatinine. I now have 8 blood tests that correspond to dietary data, and interestingly, there is a moderately strong correlation between my average daily beef+egg+cheese intake with creatinine (r = 0.55). Based on these data, I’m going to continue to minimize consumption of these foods, with the goal of optimizing creatinine.cr mec intake

On a final note, I also expected to further reduce my CRP from 0.3 to something lower, but it slightly increased to 0.37 mg/L. While that is far from a high value, lower is better, and in future blood tests I’ll try to figure out how to further reduce it.

If you’re interested in calculating your biological age, here’s the Excel link:

DNAmPhenoAge_gen (1)

 

Quantifying Biological Age: Checklist

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/

 

1.7 Years of Biological Aging In The Past 3.6 Years

In an earlier post (https://michaellustgarten.wordpress.com/2018/06/26/maximizing-health-and-lifespan-is-calorie-restriction-essential/), I documented my aging.ai biologic age for 13 blood test measurements from 2016 – 2019. If you missed that post, here are those data:
agingai2Note that note my average biologic age has slowly increased from 2016 to 2019, from 28y in 2016 (2 measurements), to 29.25y in 2017 (6 measurements), to 29.5y in 2018 (6 measurements), to 30y in my June 2019 measurement.

To gain more insight into my 2019 prediction for biologic age, I kept measuring. On September 17, 2019, I had my worst biological age to date, 33y, based on the blood test data below:
Screen Shot 2019-11-03 at 3.51.05 PM.png

Seeing a biological age that high (for me) was the motivation that I needed to finally stick to a mild caloric restriction, which I hypothesized would positively affect my biological age. I wrote about this in my recent Phenotypic Age post (https://michaellustgarten.wordpress.com/2019/11/01/biological-age-31-3y-chronological-age-46y/). Did it work? Shown below is my blood test data for October 29th.

Screen Shot 2019-11-03 at 4.07.28 PM

Based on that data, my biological age was 28y, and when averaging the 3 measurements in 2019 (so far!), my average biological age is 29.67y. When considering that my average biological age in 2016 was 28y, it looks like I’ve only aged ~1.7 years in 3.58 years of elapsed time!

 

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

Biological Age = 31.3y, Chronological Age= 46y

On June 10, 2019 (for the first time) I measured all of the blood test variables that are included in the biologic age calculator, Phenotypic Age, and ended up with a biological age = 35.39y (https://michaellustgarten.wordpress.com/2019/09/09/quantifying-biological-age/).

While that value is 23% younger than my chronological age (46y), I knew that I could do better! So I tried again on September 17, 2019. Basically, the same biological age, 35.58y:

pheno 8_2019.png

An 23% younger biological age on 2 separate dates, months apart might be good for most, but not for me. So, I tried again on October 29th, 2019, and voila, a biological age of 31.3y, which is 32% younger than my chronological age! How did I do it?

oct pheno.png

From my last blood test until my most recent blood test, I attempted a mild caloric restriction. To maintain my body weight, I require about 2800 calories per day, an amount which is based on daily body weight weighing in conjunction with daily dietary tracking. For the period of time that elapsed between my last 2 blood tests, I averaged 2657 calories/day, which is 3.2% less than the 2745 calories/day that I averaged for the dietary period that corresponded to my September blood test. That I was also in a very mild caloric restriction is confirmed by a reduction in my average body weight, which was (purposefully) down 0.7 lbs from September 17 to October 29th, when compared with the dietary period that corresponded to my September blood test (August 20 – September 17).

This is a superficial analysis of how I further reduced my biological age, but in future posts I’ll report the average dietary intake that corresponded to my relatively youthful biologic age!

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

Optimizing Biological Age: Alkaline Phosphatase

Alkaline phosphatase (ALP) is one of the 10 variables used to quantify biological age with PhenoAge (https://michaellustgarten.wordpress.com/2019/09/09/quantifying-biological-age). The reference range for alkaline phosphatase is 20 – 140 IU/L*, but within that range, what’s optimal?

Two separate meta-analyses have investigated the association between serum levels of ALP with risk of death for all causes. First, in a meta-analysis of 4 studies that included ~9 million adults, ALP values greater than 48 IU/L were associated with a significantly increased all-cause mortality risk (Kunutsor et al. 2014):

Screen Shot 2019-10-06 at 1.30.37 PM

In another meta-analysis that included 24 studies and 147,634 subjects (Li et al. 2014), lowest risk of death for all causes was identified for ALP values ~50 IU/L:

Screen Shot 2019-10-05 at 8.00.38 AM

Note that mortality risk increased linearly up to 85 U/L (short dashed line, dark black line), but increased at a much greater rate for values greater than 85 U/L. In addition, the meta-analysis of Li et al. 2014 did not include the 8.9 million adults of Fulks et al. (2008), which were included in the Kunutsor meta-analysis. Nonetheless, the data from these 2 complimentary meta-analyses arrive at the same conclusion: lower ALP values may be better in terms of reducing risk of death from all causes.

Investigating further, ALP levels increase during aging from ~60-80 U/L in adults < 55y to > 80 U/L in adults > 55y (Strømme et al. 2005, Han et al. 2016), evidence that further suggests that lower may be better:

Screen Shot 2019-10-06 at 12.36.55 PM

What are my ALP values? As shown below, I’ve measured ALP 27 times over the past 13 years, with an average value of 49.4 U/L (black line). Also note the red dotted trend line, which is close to flat over that period. So far, so good for ALP!

alp

*Note that IU/L = U/L

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

References

Fulks M, Stout RL, Dolan VF. Using liver enzymes as screening tests to predict mortality risk. J Insur Med 2008;40:191–203.

Han L, Wang J, Zhang Q, Ke P, Wu X, Wan Z, Lin H, Zeng R, Huang X, Zhuang J. Development of reference intervals for serum alkaline phosphatase among adults in Southern China traced to the new IFCC reference measurement procedure. Clin Chem Lab Med. 2016 Apr;54(4):659-65. doi: 10.1515/cclm-2015-0732.

Kunutsor SK, Apekey TA, Seddoh D, Walley J. Liver enzymes and risk of all-cause mortality in general populations: a systematic review and meta-analysis. Int J Epidemiol. 2014 Feb;43(1):187-201.

Li JW, Xu C, Fan Y, Wang Y, Xiao YB. Can serum levels of alkaline phosphatase and phosphate predict cardiovascular diseases and total mortality in individuals with preserved renal function? A systemic review and meta-analysisPLoS One. 2014 Jul 17;9(7):e102276.

Strømme JH, Rustad P, Steensland H, Theodorsen L, Urdal P. Reference intervals for eight enzymes in blood of adult females and males measured in accordance with the International Federation of Clinical Chemistry reference system at 37 degrees C: part of the Nordic Reference Interval Project. Scand J Clin Lab Invest. 2004;64(4):371-84. Erratum in: Scand J Clin Lab Invest. 2005;65(1):83-4.