Tag Archives: blood testing

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:

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?

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 With Aging.ai: Platelets

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Platelets are one of the 19 variables that are included in the biological age calculator, aging.ai. The reference range is 150-400 platelets per nanoliter (*10^9/L), but within that range, what’s optimal?

In a study of 21,635 adults older than 35y (average age wasn’t reported), platelets between 230-270 were associated with a maximally reduced risk of death from all causes (Bonaccio et al. 2016):

Similarly, in a study of 21,252 adults (average age 53y), values ~250 were associated with maximally reduced risk of death from all causes Vinholt et al. (2017) :

What about in older adults? In a study of 159,746 postmenopausal women (average age, 63y), maximally reduced risk of death from all causes was associated with platelet values between 200-256 (Kabat et al. 2017).

In a smaller study (36,262 older adults, average age, 71y), platelet values ~250 were associated with maximally reduced risk for all-cause mortality. Interestingly, even at platelet values ~250, mortality risk was highest for non-Hispanic whites, when compared with lower mortality risk for non-Hispanic blacks and Hispanics (Msaouel et al. 2014):

In 5,766 older adults (average age, 73y), platelets higher than 200-300 was associated with an increased risk of death from all causes (van der Bom et al 2009). Risk for values between 100-199 was not different when compared against 200-299, but there was a non-significant trend towards increased risk (1.05, 95% CI: 0.97, 1.14).

In 131,308 older adults (~73y), maximally reduced risk of death from all causes was associated with platelet values between 200-300, whereas risk significantly increased below and above that range, respectively Tsai et al. (2015):

In sum, the data suggests that platelet values ~250 may be optimal for heath, with 200-300 as the “optimal range” within the 150-400 reference range. What are my values? Over the past 16 years, I’ve measured my platelets 25 times, and 6x, my platelets were below this 200-300 range. I’m not too worried about it, though, as most of my measurements are within that range!

Are there any variables that are correlated with platelets? For me, the strongest correlation over 18 tracked blood tests from 2015 – 2019 is my body weight. As my weight increases, my platelets are higher (r = 0.64, p-value = 0.006). Platelets have been reported to increase in association with elevated inflammation (CRP; Izzi et al. 2018), but I only have 3 co-measurements for CRP with platelets. I have a blood test scheduled for next week, more data coming soon!

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

References

Bonaccio M, Di Castelnuovo A, Costanzo S, De Curtis A, Donati MB, Cerletti C, de Gaetano G, Iacoviello L; MOLI-SANI Investigators. Age-sex-specific ranges of platelet count and all-cause mortality: prospective findings from the MOLI-SANI study. Blood. 2016 Mar 24;127(12):1614-6.

Izzi B, Bonaccio M, de Gaetano G, Cerletti C. Learning by counting blood platelets in population studies: survey and perspective a long way after Bizzozero. J Thromb Haemost. 2018 Sep;16(9):1711-1721. doi: 10.1111/jth.14202.

Kabat GC, Kim MY, Verma AK, Manson JE, Lin J, Lessin L, Wassertheil-Smoller S, Rohan TE. Platelet count and total and cause-specific mortality in the Women’s Health Initiative. Ann Epidemiol. 2017 Apr;27(4):274-280.

Msaouel P, Lam AP, Gundabolu K, Chrysofakis G, Yu Y, Mantzaris I, Friedman E, Verma A. Abnormal platelet count is an independent predictor of mortality in the elderly and is influenced by ethnicity. Haematologica. 2014 May;99(5):930-6.

Tsai MT, Chen YT, Lin CH, Huang TP, Tarng DC; Taiwan Geriatric Kidney Disease Research Group. U-shaped mortality curve associated with platelet count among older people: a community-based cohort study. Blood. 2015 Sep 24;126(13):1633-5.

Vinholt PJ, Hvas AM, Frederiksen H, Bathum L, Jørgensen MK, Nybo M. Thromb Res.Platelet count is associated with cardiovascular disease, cancer and mortality: A population-based cohort study. 2016 Dec;148:136-142.

Sarcopenia, Disease Risk, And The Neutrophil/Lymphocyte Ratio

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In an earlier post, based on data from the Baltimore Longitidunal Study on Aging (BLSA), I suggested that total white blood cell (WBCs) counts between 3500 to 6000 cells per microliter of blood may be optimal for reducing disease risk and for maximizing longevity (https://michaellustgarten.wordpress.com/2015/08/13/blood-testing-whats-optimal-for-wbc-levels/).

However, within WBCs, neutrophils increase, whereas lymphocytes decrease during aging (Ruggiero et al. 2007, Starr and Dreary 2011). As a result, the ratio between neutrophils with lymphocytes (NLR) increases during aging from ~1.5 in 20 year olds to ~1.8 in adults older than 75y (Li et al. 2015):

An increased neutrophil/lymphocyte ratio during aging may be bad for health and disease risk. First, a higher neutrophil/lymphocyte ratio is associated with sarcopenia (defined as the age-related loss of muscle mass and physical function) in older adults (average age, 72y; Öztürk et al. 2018):

Second, risk of death for all causes is significantly increased for older adults (average age, 66y) that had higher NLR values (60-80%, >80%, equivalent to NLR = 1.92-2.41, > 2.41), when compared with lower NLR values (< 20%, 20-40%, 40-60%, equivalent to NLR < 1.90; Fest et al. 2019):

Similarly, all-cause mortality risk was 30% increased in older adults (average age, 54y) that had NLR values > 1.77, when compared with < 1.77, and 40% increased for NLR values > 2.15, when compared with < 2.15 (Kime et al. 2018).

What are my NLR values? Over 17 blood test measurements from 2015 – 2019, my average NLR is 1.11. So far so good!

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

References

Fest J, Ruiter TR, Groot Koerkamp B, Rizopoulos D, Ikram MA, van Eijck CHJ, Stricker BH. The neutrophil-to-lymphocyte ratio is associated with mortality in the general population: The Rotterdam Study. Eur J Epidemiol. 2019 May;34(5):463-470.

Kim S, Eliot M, Koestler DC, Wu WC, Kelsey KT. Association of Neutrophil-to-Lymphocyte Ratio With Mortality and Cardiovascular Disease in the Jackson Heart Study and Modification by the Duffy Antigen Variant. JAMA Cardiol. 2018 Jun 1;3(6):455-462. doi: 10.1001/jamacardio.2018.1042.

Li J, Chen Q, Luo X, Hong J, Pan K, Lin X, Liu X, Zhou L, Wang H, Xu Y, Li H, Duan C. Neutrophil-to-Lymphocyte Ratio Positively Correlates to Age in Healthy Population. J Clin Lab Anal. 2015 Nov;29(6):437-43. doi: 10.1002/jcla.21791.

Öztürk ZA, Kul S, Türkbeyler İH, Sayıner ZA, Abiyev A. Is increased neutrophil lymphocyte ratio remarking the inflammation in sarcopenia? Exp Gerontol. 2018 Sep;110:223-229.

Ruggiero C, Metter EJ, Cherubini A, Maggio M, Sen R, Najjar SS, Windham GB, Ble A, Senin U, Ferrucci L. White blood cell count and mortality in the Baltimore Longitudinal Study of Aging. J Am Coll Cardiol. 2007 May 8;49(18):1841-50.

Starr JM, Deary IJ. Sex differences in blood cell counts in the Lothian Birth Cohort 1921 between 79 and 87 years. Maturitas. 2011 Aug;69(4):373-6.

Blood glucose: What’s optimal?

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The reference range for circulating levels of glucose is 70-130 mg/dL. That’s a wide range, so what’s optimal, especially considering that glucose is one of the variables used to quantify of biological age (https://michaellustgarten.wordpress.com/2019/09/09/quantifying-biological-age)?

In the largest study published for this subject (12,455,361 adults), risk of death for all causes was maximally reduced for glucose levels between 80-94 mg/dL (Yi et al. 2017). In contrast, mortality risk significantly increased when glucose levels were < 80 or > 100 mg/dL in both men and women:

As glucose levels rise above 100 mg/dL, risk for Type II diabetes increases, which is one potential explanation for higher glucose levels being associated with a higher mortality risk. Why would glucose levels lower than 80 mg/dL also be associated with worse health? Interestingly, glucose levels < 80 mg/dL are associated with an increased risk of death from “total external causes” (left panel below), including unintentional accidents and transport accidents (middle, right panel below) in a relatively large study of 345,318 adults (Yi et al. 2019). In addition, an increased mortality risk from transport accidents involving pedestrians or cyclists was associated with glucose levels below 55 mg/dL (data not shown):

Glucose levels increase during aging (Yi et al. 2017), evidence that adds further merit that lower is better (but not below 80 mg/dL!):

What are my glucose levels? Shown below is my data for the past 13 years:

On the left side of the chart, I measured my glucose levels about once per year from 33-40y, resulting in an average value of 89 mg/dL. Since 2015 I started daily dietary tracking, and tested more often (19x), resulting in an average value of 87 mg/dL. The comparison between these 2 groups of data is not significantly different (p=0.19). Based on the data in Yi et al., my glucose levels should have increased from 92 to 96 mg/dL during the past 13 years. Instead, my glucose levels during that period are relatively stable, with average value (87.5 mg/dL) that would be expected for a 26y old. So far, so good!

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

References

Yi SW, Park S, Lee YH, Park HJ, Balkau B, Yi JJ. Association between fasting glucose and all-cause mortality according to sex and age: a prospective cohort study. Sci Rep. 2017 Aug 15;7(1):8194. doi: 10.1038/s41598-017-08498-6.

Yi SW, Won YJ, Yi JJ. Low normal fasting glucose and risk of accidental death in Korean adults: A prospective cohort study. Diabetes Metab. 2019 Jan;45(1):60-66. doi: 10.1016/j.diabet.2018.01.005.

Ending Aging-Related Diseases 2019: Lustgarten Presentation

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In the first half of this presentation, I talk about my contribution to the gut-muscle axis in older adults, and in the second half, my personalized approach to optimal health!

Also, here’s the article that corresponds to the presentation:
https://www.leafscience.org/the-gut-microbiome-affects-muscle-strength-in-older-adults/

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

Optimizing Biological Age: RDW%

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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.

LP(a), cardiovascular disease, and all-cause mortality: What’s optimal?

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Very low, low, and high-density lipoproteins (VLDL, LDL, HDL, respectively) are commonly measured on the standard blood chemistry panel as measures of cardiovascular disease risk. Not included on that panel is another lipoprotein, Lp(a), which is a modified form of LDL. What’s the relationship between Lp(a) with disease risk?

A meta-analysis of 36 studies that included 126,634 subjects reported that Lp(a) > 30 mg/dL (65 nmol/L) was significantly associated with an increased risk for heart attacks, coronary heart disease-related deaths, and ischemic strokes (Erqou et al. 2009):

Investigating further, of 2,100 candidate genes that were evaluated for predicting heart disease risk, genetic variation in the LPA gene was the strongest genetic risk factor (Clarke et al. 2009). Of the Lp(a)-related genes, SNPs for rs3798220 (increased risk allele = C) and rs10455872 (increased risk allele = G) were associated with a 92% and a 70% increased risk for coronary heart disease, respectively.

Based on these data, Lp(a) values less than 50 mg/dL (108 nmol/L) have been recommended, with 1-3 grams/day of niacin, which reduces Lp(a) levels, as the primary treatment for minimizing cardiovascular disease risk (Nordestgaard et al. 2010).

However, cardiovascular disease is only 1 outcome. What’s the data for Lp(a) and risk of death from all causes, not just cardiovascular disease-related deaths? In a study of 10,413 adults (average age, 55y), the lowest risk of death from all causes was reported for Lp(a) values of 270 mg/L (equivalent to 27 mg/dL, and 58 nmol/L). The log of 270 is 2.43, which corresponds to the lowest mortality risk on the chart below (Sawabe et al. 2012):

Interestingly, all-cause mortality risk was significantly increased only for Lp(a) values < 80 mg/L (log 80 = 1.90; equivalent to 17 nmol/L), when compared with intermediate (80 – 550 mg/L; log values from 1.9 – 2.7 on the chart; equivalent to 17 – 118 nmol/L) and high Lp(a) (> 550 mg/L; log values > 2.7 on the chart; equivalent to > 118 nmol/L).

In addition to low Lp(a) values, an increased risk of death from all causes (and a shorter lifespan) have also been reported for high Lp(a). When compared with Lp(a) < 21 nmol/L, Lp(a) > 199 nmol/L was associated with a 20% increased all-cause mortality risk (Langsted et al. 2019). In addition, median lifespan was 1.4 years shorter for subjects that had Lp(a) values > 199 nmol/L, when compared with < 21 nmol/L.

Based on the studies of Sawabe and Langsted, both low and high Lp(a) values may be bad for disease risk. What are my Lp(a) values?

I’ve been tracking Lp(a) for the past 14 years, first, approximately 1x/year until I was 40, and second, 9 times since 2015, when I started daily nutrition tracking. In addition, I’ve measured it 4x in 2019, with the goal of getting it closer to the 58 nmol/L value of the Sawabe study. When I first started measuring Lp(a) in 2005, it was ~150 nmol/L, which is way higher than the < 65 nmol/L that was reported for reduced cardiovascular disease risk in the Erqou meta-analysis, and the 58 nmol/L value that was reported for maximally reduced all-cause mortality risk in the Sawabe study:

Fortunately, I was able to reduce my Lp(a) levels from those first values to levels closer to ~100 nmol/L, which is still too high. For the first 8 Lp(a) measurements, I didn’t track my nutrition, so I can’t say which factors helped me to reduce it. Also, note that I didn’t include the blood test measurement where I tried high dose niacin (3 g/day), which reduced my Lp(a) to 84 nmol/L, but also worsened my liver function,. My liver enzymes, AST and ALT doubled on high-dose niacin! What good is a reduced risk for cardiovascular disease if my risk for liver disease simultaneously goes up? Obviously, I quickly discontinued use of niacin to reduce Lp(a).

Also note the data on the chart since 2015, when I started daily nutritional tracking. Over that period, my average value over 9 Lp(a) measurements is 95.3 nmol/L. Although my average Lp(a) is still higher than it should be, it’s better than my pre-tracking Lp(a) average value of 115.6 nmol/L (p-value = 0.03 for the between-group comparison). In addition, on my last 3 measurements, my Lp(a) values were 75, 82, and 79 nmol/L. How have I been reducing it?

As I’ve mentioned in many blog posts, I’ve been weighing, logging, and tracking my nutrient intake since 2015. When I blood test, I can use the average dietary intake that corresponds to the blood test result, and with enough blood test results, I can look at correlations between my diet with blood test variables. Based on this approach, one possibility is my daily sodium intake. Shown below is a moderately strong correlation (r = 0.61, R^2 = 0.366) between my daily sodium intake with Lp(a). The higher my sodium intake, the lower my Lp(a) values.

Can the strength of this approach be improved? Interestingly, I identified another moderately strong correlation (r = 0.69) between my lycopene intake with Lp(a): the higher my lycopene intake, the higher my Lp(a)! I then decided to include both sodium and lycopene in a linear regression model, and the correlation for both of these nutrients with Lp(a) is 0.90! So what will I do with this info?

The highest that my average dietary sodium intake has been in any blood testing period is ~2500 mg. Sodium levels higher than that seem to negatively affect my sleep, so I’m not interested in going higher than 2500 mg/day. Also, there may be a plateau effect for sodium, as values ~2500 mg/day didn’t associate with significantly lower Lp(a) values when compared with 2300 mg/day. I can, in contrast, reduce my lycopene intake, which comes almost exclusively from my daily watermelon intake. I usually eat ~7 oz/day, and for my next blood test I’ll reduce this to 5 oz/day. Based on the regression equation that includes sodium and lycopene, with a 2300 mg sodium intake and the amount of lycopene that corresponds to 5 oz. of daily watermelon (~6700 micrograms, down from ~9000 micrograms), I should expect to see a Lp(a) value ~67 nmol/L on my next blood test. If not, I’ll repeat this approach, looking for strong correlations between my diet with Lp(a), followed by tweaking my diet to obtain biomarker results that are close to optimal. Stay tuned my my next blood test data, coming in about 2 weeks!

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

References

Clarke, R., J. F. Peden, J. C. Hopewell, T. Kyriakou, A. Goel, S. C. Heath, S. Parish, S. Barlera, M. G. Franzosi, S. Rust, et al. 2009. Genetic variants associated with Lp(a) lipoprotein level and coronary disease. N. Engl. J. Med. 361: 2518–2528.

Erqou, S., S. Kaptoge, P. L. Perry, A. E. Di, A. Thompson, I. R. White, S. M. Marcovina, R. Collins, S. G. Thompson, and J. Danesh. 2009. Lipoprotein(a) concentration and the risk of coronary heart disease, stroke, and nonvascular mortality. JAMA. 302: 412–423.

Langsted A, Kamstrup PR, Nordestgaard BG. High lipoprotein(a) and high risk of mortality. Eur Heart J. 2019 Jan 4. [Epub ahead of print].

Sawabe M, Tanaka N, Mieno MN, Ishikawa S, Kayaba K, Nakahara K, Matsushita S; JMS Cohort Study Group. Low Lipoprotein(a) Concentration Is Associated with Cancer and All-Cause Deaths: A Population-Based Cohort Study (The JMS Cohort Study). PLoS One. 2012; 7(4): e31954. PLoS One. 2012;7(4):e31954.

Nordestgaard BG, Chapman MJ, Ray K, Borén J, Andreotti F, Watts GF, Ginsberg H, Amarenco P, Catapano A, Descamps OS, Fisher E, Kovanen PT, Kuivenhoven JA, Lesnik P, Masana L, Reiner Z, Taskinen MR, Tokgözoglu L, Tybjærg-Hansen A; European Atherosclerosis Society Consensus Panel. Lipoprotein(a) as a cardiovascular risk factor: current status. Eur Heart J. 2010 Dec;31(23):2844-53.

Reducing Homocysteine? Updates.

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In an earlier post I wrote about the association between elevated circulating levels of homocysteine with an increased risk of death from all causes (https://michaellustgarten.wordpress.com/2017/11/22/homocysteine-and-all-cause-mortality-risk/). I started to post updates in that link, but I’ve decided to move them to here.

As of 6/2018, I now have tracked dietary data (I weigh all my food and record the values in cronometer.com) that corresponds to 7 homocysteine measurements:

12/5/2017: Despite 42 days of 800 micrograms of supplemental folic acid, bringing my average daily folate intake to 2026 micrograms/day, my plasma homocysteine was essentially unchanged at 11.7 uMoL, when compared with my baseline value of 11.8 uMol.What’s next on the list to reduce it? Trimethylglycine, also known as betaine. I’m a proponent of using diet as a first strategy, and to increase my dietary betaine levels, I’ll eat beets and quinoa, bringing my daily betaine levels to ~500 mg/day. Let’s see how it turns out on my next blood test!

1/2/2018: ~500 mg/day of betaine from beets and quinoa did absolutely nothing to my homecysteine levels. In fact, it got worse (15.3 uMoL)! To test the hypothesis that it wasn’t enough betaine, next I tried 4 grams/day of betaine (also known as trimethylglycine, TMG).

2/20/18: Supplemental TMG did absolutely nothing in terms of reducing my homocysteine to values below baseline! Also note that there is evidence that TMG increases blood lipids, including LDL and triglycerides (TG; Olthof et al. 2005), and that’s exactly what it did to me. My average LDL and TG values since 2015 (11 measurements) are 77 and 50 mg/dL, respectively. On TMG, these values increased to 92 and 72 mg/dL, respectively, making them my highest values over 11 individual blood tests (with the exception of 1 day with an LDL of 93 mg/dL). Next, I tried a stack that included 50 mg of B6, 1000 mcg of B12, and 400 mcg of methylfolate, as supplementation with these B-vitamins has been shown to lower homocystine (Lewerin et al. 2003).

3/20/18: Finally, some progress! My homocysteine levels were reduced during the B-vitamin supplementation period. I’ve written it like that because I’m not sure if it was the B-vitamins that caused it. For example, in the image below, we see the correlation between my dietary B6 intake with homocysteine. The trendline is down, which I would expect if B6 supplementation actually is playing a role in reducing my homocysteine levels. However, note that the correlation between my dietary B6 levels with homocysteine is not very strong (r = .48), resulting in a moderate R2 of 0.23 (similar data was obtained for B12 and folate). With 5 blood test measurements corresponding to 5 dietary periods, if B6 is playing a role, I would expect a stronger correlation. Nonetheless, with more data, the correlation may strengthen, so stay tuned for that!

5/14/2018: I changed B6-B12-methylfolate supplements so that I’d only have to take pills from 1 bottle instead of from 3. That supplement, however, had 1.5 mg of B6 instead of the 50 mg that was in my original supplement. Less B6 didn’t result in a higher homocysteine value-in fact, it went down (slightly), from 10.8 to 10.6. If an increased amount of B6 was causing lower levels of homocysteine, I would’ve expected higher, not (barely) lower homocysteine levels. This suggests that maybe my B6 intake has nothing to do with my homocysteine levels.

6/4/2018: Despite no changes to my supplements, my homocysteine came down a little more, to 10.2. Interestingly, the correlation (r) between homocysteine with my total dietary (diet + supplements) intake of B6, B12, and methylfolate is 0.39, 0.68, 0.29, respectively. The correlation between my B12 intake with homocysteine looks moderately strong, whereas the correlations for B6 and folate are weak. Based on this data, it’s possible I had a mild B12 deficiency that was causing elevated homocysteine. Note that my average B12 intake, without supplements is ~8 mcg/day, which is more than 3-fold higher than the RDA.

In looking at the association between my dietary data with homocysteine, a stronger correlation (r = 0.91; R2 = 0.83) has emerged…for my protein intake! In other words, a higher protein intake is more strongly correlated with lower homocysteine than B12:

7/11/2018: To explore the strong association between my protein intake with homocysteine, I increased my protein intake from an average value of 104 g/day for the period that preceded my June measurement (5/15/2018 – 6/4/2018) to 136 g/day for the period up to my 7/11/2018 measurement (6/5/2018 – 7/10/2018). The result? Lower homocysteine, to 8.2 uMol/L! Interestingly, the correlation between my dietary protein intake with homocysteine remained strong (r = 0.86, R2 = 0.73, n = 7 measurements).

What about my B6, methyl-B12, methyl-folate stack? I’m still taking it, although it looks like methyl-B12 may be the only factor that is associated with my homocysteine levels. In support of that, the correlation between each with homocysteine is r = 0.02, 0.73, 0.36, respectively.

Because I now have my homocysteine < 9 umol/L, it may be time to optimize other variables (in addition to the metabolic panel and CBC). Stay tuned!

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

References

Lewerin C, Nilsson-Ehle H, Matousek M, Lindstedt G, Steen B. Reduction of plasma homocysteine and serum methylmalonate concentrations in apparently healthy elderly subjects after treatment with folic acid, vitamin B12 and vitamin B6: a randomised trial.vEur J Clin Nutr. 2003 Nov;57(11):1426-36.

Olthof MR, van Vliet T, Verhoef P, Zock PL, Katan MB. Effect of homocysteine-lowering nutrients on blood lipids: results from four randomised, placebo-controlled studies in healthy humans. PLoS Med. 2005 May;2(5):e135.

Homocysteine and All-Cause Mortality Risk

18 Replies

On a recent blood test, my plasma level of homocysteine (Hcy) was 11.9 uMol. Is that optimal minimizing disease risk and maximizing longevity? Let’s have a look at the literature.

A 2017 meta-analysis of 11 studies including 27,737 participants showed an increased risk of death from all causes (“all-cause mortality”; ACM) as circulating levels of homocysteine increase (Fan et al. 2017):

When looking at meta-analyses, it’s important to examine each of the individual studies. Here are the data for the 11 included studies:

Kark et al. 1999: 1,788 older adults, average age 65y, followed for 9-11 years. Compared with values less than 8.5 uMol, subjects with elevated homocysteine (> 14.7) had a 2-fold higher risk of death from all causes.
Bostom et al. 1999: 1,933older adults, verage age, 70y, median follow-up, 10y. Subjects with values > 14.3 uMol had 2-fold ACM risk, when compared with < 14.3.
Hoogeveen et al. 2000: 811 older adults (average age, 65y), 5 yr follow-up. Non- diabetics had a 34% increased ACM risk (p=0.08), but diabetics had 2.5-fold increased ACM risk after a 5-yr follow-up.
Vollset et al. 2001: 4,766 older adults (age range, 65-67y at study entry), median 4 yr follow-up. Compared with 5.1-8.9 uMol, values greater than 12 were significantly associated with a 2.4-4.5 increased ACM risk.
Acevedo et al. 2003. 3,427 subjects, average age 56y, ~3yr follow-up. ACM risk lowest for < 9.4 uMol, compared with > 14.4.
González et al. 2007: 215 older adults (average age, 75y), median 4 yr follow-up. Compared with < 8.7 uMol, values > 16.7 had 2.3-fold increased ACM risk.
Dangour et al. 2008: 853 older adults (average age, 79y), ~7.6y follow-up. Homocysteins > 19.4 uMol associated with ~2-fold higher ACM risk, when compared with < 9.8.
Xiu et al. 2012: 1,412 older adults (average age, ~75y), up to 10 year follow-up. 1.8-fold higher ACM risk comparing those with >14.5 uMol with < 9.3.
Waśkiewicz et al. 2012: 7,165 middle aged adults, ~5yr follow- up. 1.8-fold increased ACM risk for subjects with homocysteine > 10.5 uMol(average age, 52y) when compared with < 8.2 (avg age, 40y).
Wong et al. 2013: 4,248 older men, average age ~77y, ~5yr follow-up. 1.5-fold increased ACM risk for homocysteine values > 15 uMol.
Swart et al. 2012: 1,117 older adults (average age, 75y), up to a 7yr follow-up. In 543 men, homocysteine was not associated with ACM risk. In 574 women, 1.7 to 1.9-fold higher ACM risk when comparing > 12.7 and >15.6 vs < 10.3 uMol.

Not included in their analysis:

Petersen et al. 2016: 670 subjects, average age 65y, average follow-up 14.5y. Subjects with homocysteine values ≥ 10.8 μmol/l had a significant higher incidence of all-cause mortality:

In sum, the evidence appears consistent across these 12 studies that elevated homocysteine is associated with an increased risk of death from all causes. Based on the Fan et al. (2016) meta-analysis, lower appears better, with values < 5 uMol associated with maximally reduced ACM risk. Also based on that data, my ACM risk is ~1.5-fold increased!

To see how dietary changes and supplements have impacted my homocysteine levels, see this link: https://michaellustgarten.wordpress.com/2018/03/23/reducing-homocysteine-updates/

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

References:

Bostom AG, Silbershatz H, Rosenberg IH, Selhub J, D’Agostino RB, Wolf PA, Jacques PF, Wilson PW. Nonfasting plasma total homocysteine levels and all-cause and cardiovascular disease mortality in elderly Framingham men and women. Arch Intern Med. 1999 May 24;159(10):1077-80.

Dangour AD, Breeze E, Clarke R, Shetty PS, Uauy R, Fletcher AE. Plasma homocysteine, but not folate or vitamin B-12, predicts mortalityin older people in the United Kingdom. J Nutr. 2008 Jun;138(6):1121-8.

Fan R, Zhang A, Zhong F. Association between Homocysteine Levels and All-cause Mortality: A Dose-Response Meta-Analysis of Prospective Studies. Sci Rep. 2017 Jul 6;7(1):4769.

González S, Huerta JM, Fernández S, Patterson AM, Lasheras C. Homocysteine increases the risk of mortality in elderly individuals. Br J Nutr. 2007 Jun;97(6):1138-43.

Hoogeveen EK, Kostense PJ, Jakobs C, Dekker JM, Nijpels G, Heine RJ, Bouter LM, Stehouwer CD. Hyperhomocysteinemia increases risk of death, especially in type 2 diabetes : 5-year follow-up of the Hoorn Study. Circulation. 2000 Apr 4;101(13):1506-11.

Kark JD, Selhub J, Adler B, Gofin J, Abramson JH, Friedman G, Rosenberg IH. Nonfasting plasma total homocysteine level and mortality in middle-aged and elderly men and women in Jerusalem. Ann Intern Med. 1999 Sep 7;131(5):321-30.

Petersen JF, Larsen BS, Sabbah M, Nielsen OW, Kumarathurai P, Sajadieh A. Long-term prognostic significance of homocysteine in middle-aged and elderly. Biomarkers. 2016 Sep;21(6):490-6.

Swart KM, van Schoor NM, Blom HJ, Smulders YM, Lips P. Homocysteine and the risk of nursing home admission and mortality in older persons. Eur J Clin Nutr. 2012 Feb;66(2):188-95.

Waśkiewicz A, Sygnowska E, Broda G. Homocysteine concentration and the risk of death in the adult Polish population. Kardiol Pol. 2012;70(9):897-902.

Wong YY, Almeida OP, McCaul KA, Yeap BB, Hankey GJ, Flicker L. Homocysteine, frailty, and all-cause mortality in older men: the health in men study. J Gerontol A Biol Sci Med Sci. 2013 May;68(5):590-8.

Vollset SE, Refsum H, Tverdal A, Nygård O, Nordrehaug JE, Tell GS, Ueland PM. Plasma total homocysteine and cardiovascular and noncardiovascular mortality: the Hordaland Homocysteine Study. Am J Clin Nutr. 2001 Jul;74(1):130-6.

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