Tag Archives: Disease Risk

HDL Update: Age-Related Changes, All-Cause Mortality Risk, And Progress Towards The Optimal Range

In November 2020, I made a HDL video based on a meta-analysis in ~3.4 million subjects that was published in July 2020. In Dec 2020, a larger study (n=15.8 million subjects) was published-those data are presented in the video, and compared against the meta-analysis.

In addition, I’ve tested my HDL 2 more times since November 2020, so how’s my progress for getting it into the optimal range? Also, I attempt to derive clinical significance by identifying correlations for higher HDL with lower Lp(a) and hs-CRP.

Video link: https://www.youtube.com/watch?v=MUuKlpyvZaU

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

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?

Uric acid: What’s optimal?

The reference range for uric acid is 4.0 – 8 mg/dL for men, and 2.5 – 7 mg/dL for women. Are these values optimal for health? To answer that question, let’s have a look at how circulating levels of uric acid change during aging, and their association with risk of death for all causes.

Uric acid increases during aging in both men and women. Kuzuya et al. (2002) studied how uric acid changes during a 10-year intervals for various birth cohorts, including 32yr olds, 39yr olds, 47yr olds, 56yr olds, and 65 yr olds (1960-1969, 1950-1959, 1940-1949, 1930-1939, 1920-1929 birth cohorts, respectively). For each birth cohort, uric acid levels increased during aging for men (left image below), whereas they increased for women starting at 40 years old:

Screen Shot 2020-01-06 at 7.18.04 AM

In terms of mortality risk, lowest risk of death for all causes was associated with uric acid levels of 5 – 7 mg/dL for men and 4 – 6 mg/dL for women in the 9,118 adults (average age, 43y) of Hu et al. (2019). Also note the U-shaped curve for both genders, whereas mortality risk increases at both low and high levels of uric acid:

Screen Shot 2020-01-05 at 2.55.00 PM.png

Similarly, the lowest risk of death for all causes was associated with uric acid levels of 7 mg/dL for men, and 4 mg/dL for women in the 375,163 adults (average age, 40y) of Cho et al. (2018), with mortality risk significantly increasing at uric levels < 3.5 and > 9.5 mg/dL for men, < 2.5 and > 7.5 mg/dL for women. Collectively, these 2 studies in middle-aged adults suggest that uric acid levels ~ 4 mg/dL for women and ~7 for men may be optimal for reducing risk of disease for all causes. It’s also important to note that both low and higher values are associated with an increased mortality risk.

The data for the Hu and Chu studies are in younger adults, so how does the data look in older adults? Lowest all-cause mortality risk was associated with uric acid levels between 4 – 5 mg/dL in the 121, 771 older adults (average age, 73y) of Tseng et al. (2018), with mortality risk significantly increasing below 4 and > 8:

Screen Shot 2020-01-05 at 2.43.46 PM.png

What are my uric acid levels? From 2016 to 2018, I measured it 15x, and although my average value of 5.2 mg/dL is not too low or too high in terms of an increased all-cause mortality risk, it increased during that 3-year period (R2 = 0.2886). When considering that uric acid increases during aging, can I reduce it with diet?

ua ml

Because I track my daily nutritional intake, I can look for correlations between my dietary intake with circulating biomarkers. Interestingly, a moderately strong correlation between my lycopene intake with uric acid (R2 = 0.3343, p=0.024) was present from 2016 to 2018:

ua vs lyco.png

Lycopene is found almost exclusively in tomatoes and watermelon. If these foods are related to my increasing levels of uric acid, if I ate less of them, I’d expect to see a corresponding decrease in uric acid. So, in 2019, I ate less of these foods, thereby reducing my average lycopene intake from 11,585 to 9,132 micrograms per day. How did that affect circulating levels of uric acid?

In 6 measurements for 2019, my average uric acid level was 4.6 mg/dL, a value that was significantly different (p=0.02) from the 2016-2018 average of 5.2 mg/dL. Whether eating less watermelon and tomatoes caused the decrease is unknown, but it’s good to know that uric acid can be potentially modified with dietary change!

my ua


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


Cho SK, Chang Y, Kim I, Ryu S. U-Shaped Association Between Serum Uric Acid Level and Risk of Mortality: A Cohort Study. Arthritis Rheumatol. 2018 Jul;70(7):1122-1132. doi: 10.1002/art.40472.

Hu L, Hu G, Xu BP, Zhu L, Zhou W, Wang T, Bao H, Cheng X. U-Shaped Association of Serum Uric Acid with All-cause and Cause-Specific Mortality in US Adults: A Cohort Study. J Clin Endocrinol Metab. 2019 Oct 25. pii: dgz068. doi: 10.1210/clinem/dgz068.

Kuzuya M, Ando F, Iguchi A, Shimokata H. Effect of aging on serum uric acid levelslongitudinal changes in a large Japanese population group. J Gerontol A Biol Sci Med Sci. 2002 Oct;57(10):M660-4.

Tseng WC, Chen YT, Ou SM, Shih CJ, Tarng DC; Taiwan Geriatric Kidney Disease (TGKD) Research Group. U-Shaped Association Between Serum Uric Acid Levels With Cardiovascular and All-Cause Mortality in the Elderly: The Role of Malnourishment. J Am Heart Assoc. 2018 Feb 10;7(4). pii: e007523. doi: 10.1161/JAHA.117.007523.

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: C-Reactive Protein (hs-CRP)

High sensitivity C-Reactive Protein (CRP) is one of the 10 variables included in the biological age calculator, PhenoAge (https://michaellustgarten.wordpress.com/2019/09/09/quantifying-biological-age/). The reference range for CRP is 0 – 3 mg/L, but within that range, what’s optimal? To answer that question, it’s important to know how CRP changes during aging, and what levels are associated with an increased risk of death for all causes.

First, CRP increases 3-5 fold during aging in women and men, respectively (Ferrucci et al. 2005):

crp age.png

Investigating further, CRP continues to increase from relatively low levels of 0.7 mg/L (equivalent to 0.07 mg/dL) in 85-99 year olds to 2.5 mg/L (equivalent to 0.25 mg/dL) in adults older than 110y (Arai et al. 2015):

crp cent.png

In support of this finding, the average CRP level in 98 centenarians (average age, 101y) was 5.4 mg/L, when compared with 3.2 mg/L in 70 year olds (Montoliu et al. 2014).

Based on the data for how CRP changes during aging, lower values would be expected to better in terms of risk of death for all causes. How low is optimal for CRP?

Several studies have investigated this issue. Risk of death for all causes was significantly reduced when CRP was < 3 mg/L, when compared with > 3 mg/L in the 11,193 subjects (average age 63y) of Oluleye et al. (2013). In terms of CRP values less than 3 mg/L, CRP < 1.0 mg/L was associated with significantly reduced risk of death for all causes in the 5,248 subjects (average age, 54y) of Hamer et al. (2010), in the 3,620 subjects (average age, 58y) of Koenig et al. (2008), in the 2,240 older adults (average age, 69y) of Elkind et al. (2009), and in the 1,519 subjects (average age 72y) of Kuoppamäki et al. (2015).

Similarly, CRP levels close to 1 mg/dL have also been associated with a significantly reduced risk of death for all causes, including < 0.86 mg/L in the 11,409 adults (average age, 59y) of Shen et al. (2019), and < 0.83 mg/L in the 1,476 men (average age, 53y) of Laaksonen et al. (2005).

In terms of the association between CRP with risk of death for all causes, can we go lower than ~0.8 mg/L? CRP values < 0.5 mg/L were associated with reduced all-cause mortality risk, whereas values > 3 mg/L were associated with increased risk in the 16,850 non-smokers and non-users of hormone replacement therapy (average age, 58y) of Ahmadi-Abhari et al. (2013). Similarly, CRP between 0.5 – 1 mg/L, the area on the chart (see below) where the black line and the shaded 95% confidence interval have a hazard ratio < 1, was associated with a significantly reduced risk of death for all causes, whereas CRP > 5 mg/L was associated with an increased all-cause mortality risk in the 7,015 subjects of Zuo et al. (2016):

Screen Shot 2019-10-18 at 7.58.58 AM

Going even lower, CRP < 0.33 mg/L (Tertile 1, white circle) was associated with a maximally reduced all-cause mortality risk when compared with values > 0.86 mg/L (Tertile 3, black circle) in the 1,034 older adults (average age, ~72y) of Shinkai et al. (2008):

crp mortal2.png

Similarly, CRP values between 0.03 – 0.33 mg/L in men and between 0.03 – 0.25 mg/L in women (blue lines for both men and women, Tertile 1) was associated with a significantly reduced risk of death for all causes in the 11,080 subjects (average age, 62y) of Nisa et al. (2016). In contrast, CRP > 0.85 mg/L in men and > 0.62 mg/L in women (close to significance in women, p=0.06; green lines for both, Tertile 3) was associated with an increased all-cause mortality risk:

Screen Shot 2019-10-16 at 7.27.39 AM

Lowest risk of death for all causes was also identified when CRP was between 0.1 – 0.3 mg/L (1st; Tertile 1), when compared with CRP > 0.8 mg/L (3rd; Tertile 3) in the 7,740 older adults (average age, 64y) of Makita et al. (2009):

Screen Shot 2019-10-17 at 8.01.02 PM.png

Can we go lower than 0.3 mg/L for CRP and all-cause mortality risk? Yes! CRP < 0.21 mg/L was associated with a maximally reduced risk of death for all causes, and mortality risk significantly increased above 0.44 mg/L in the 2,589 subjects (average age, 59y) of Arima et al. (2008):

Screen Shot 2019-10-17 at 7.34.48 PM.png

Collectively, based on these data, with the goal of optimal health and lifespan, I’d suggest that CRP levels should be as low as possible, and avoiding the age-related CRP increase.  What are my CRP values? I’ve only measured it 6x, including once in 2009 (0.2 mg/L), once in 2018 (0.67 mg/L), and 4x in 2019 (0.41, 0.34, 0.47, 0.29 mg/L). My average value for 2019 is 0.38 mg/L, and I’d like to cut that in half. I have a blood test scheduled for next week, so stay tuned for that data!

Here’s the short version of this post in video format!


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



Ahmadi-Abhari S, Luben RN, Wareham NJ, Khaw KT. Seventeen year risk of all-cause and cause-specific mortality associated with C-reactive proteinfibrinogen and leukocyte count in men and women: the EPIC-Norfolk studyEur J Epidemiol. 2013 Jul;28(7):541-50. doi: 10.1007/s10654-013-9819-6.

Arai Y, Martin-Ruiz CM, Takayama M, Abe Y, Takebayashi T, Koyasu S, Suematsu M, Hirose N, von Zglinicki T. Inflammation, But Not Telomere Length, Predicts Successful Ageing at Extreme Old Age: A Longitudinal Study of Semi-supercentenarians. EBioMedicine. 2015 Jul 29;2(10):1549-58. doi: 10.1016/j.ebiom.2015.07.029.

Arima H, Kubo M, Yonemoto K, Doi Y, Ninomiya T, Tanizaki Y, Hata J, Matsumura K, Iida M, Kiyohara Y. Highsensitivity C-reactive protein and coronary heart disease in a general population of Japanese: the Hisayama studyArterioscler Thromb Vasc Biol. 2008 Jul;28(7):1385-91. doi: 10.1161/ATVBAHA.107.157164.

Elkind MS, Luna JM, Moon YP, Liu KM, Spitalnik SL, Paik MC, Sacco RL. High-sensitivity C-reactive protein predicts mortality but not stroke: the Northern Manhattan Study. Neurology. 2009 Oct 20;73(16):1300-7. doi: 10.1212/WNL.0b013e3181bd10bc.

Kuoppamäki M, Salminen M, Vahlberg T, Irjala K, Kivelä SL, Räihä I. High sensitive C-reactive protein (hsCRP), cardiovascular events and mortality in the aged: a prospective 9-year follow-up studyArch Gerontol Geriatr. 2015 Jan-Feb;60(1):112-7. doi: 10.1016/j.archger.2014.10.002.

Ferrucci L, Corsi A, Lauretani F, Bandinelli S, Bartali B, Taub DD, Guralnik JM, Longo DL. The origins of age-related proinflammatory state. Blood. 2005 Mar 15;105(6):2294-9. Epub 2004 Nov 30.

Hamer M, Chida Y, Stamatakis E. Association of very highly elevated C-reactive protein concentration with cardiovascular events and all-cause mortality. Clin Chem. 2010 Jan;56(1):132-5. doi: 10.1373/clinchem.2009.130740.

Koenig W, Khuseyinova N, Baumert J, Meisinger C. Prospective study of high-sensitivity C-reactive protein as a determinant of mortalityresults from the MONICA/KORA Augsburg Cohort Study1984-1998Clin Chem. 2008 Feb;54(2):335-42.

Laaksonen DE, Niskanen L, Nyyssönen K, Punnonen K, Tuomainen TP, Salonen JT. C-reactive protein in the prediction of cardiovascular and overall mortality in middle-aged men: a population-based cohort study. Eur Heart J. 2005 Sep;26(17):1783-9.

Montoliu I, Scherer M, Beguelin F, DaSilva L, Mari D, Salvioli S, Martin FP, Capri M, Bucci L, Ostan R, Garagnani P, Monti D, Biagi E, Brigidi P, Kussmann M, Rezzi S, Franceschi C, Collino S. Serum profiling of healthy aging identifies phospho- and sphingolipid species as markers of human longevity. Aging (Albany NY). 2014 Jan;6(1):9-25.

Makita S, Nakamura M, Satoh K, Tanaka F, Onoda T, Kawamura K, Ohsawa M, Tanno K, Itai K, Sakata K, Okayama A, Terayama Y, Yoshida Y, Ogawa A. Serum C-reactive protein levels can be used to predict future ischemic stroke and mortality in Japanese men from the general populationAtherosclerosis. 2009 May;204(1):234-8. doi: 10.1016/j.atherosclerosis.2008.07.040.

Oluleye OW, Folsom AR, Nambi V, Lutsey PL, Ballantyne CM; ARIC Study Investigators. Troponin TB-type natriuretic peptideC-reactive protein, and cause-specific mortality. Ann Epidemiol. 2013 Feb;23(2):66-73. doi: 10.1016/j.annepidem.2012.11.004.

Nisa H, Hirata A, Kohno M, Kiyohara C, Ohnaka K. High-Sensitivity C-Reactive Protein and Risks of All-Cause and Cause-Specific Mortality in a Japanese Population. Asian Pac J Cancer Prev. 2016;17(5):2643-8.

Shen Y, Zhang Y, Xiong S, Zhu X, Ke C. High-sensitivity C-reactive protein and cystatin C independently and jointly predict all-cause mortality among the middle-aged and elderly Chinese population. Clin Biochem. 2019 Mar;65:7-14. doi:10.1016/j.clinbiochem.2018.12.012.

Shinkai S, Chaves PH, Fujiwara Y, Watanabe S, Shibata H, Yoshida H, Suzuki T. Beta2-microglobulin for risk stratification of total mortality in the elderly population: comparison with cystatin C and C-reactive protein. Arch Intern Med. 2008 Jan 28;168(2):200-6. doi: 10.1001/archinternmed.2007.64.

Zuo H, Ueland PM, Ulvik A, Eussen SJ, Vollset SE, Nygård O, Midttun Ø, Theofylaktopoulou D, Meyer K, Tell GS. Plasma Biomarkers of Inflammation, the Kynurenine Pathway, and Risks of All-CauseCancer, and Cardiovascular Disease Mortality: The Hordaland Health Study. Am J Epidemiol. 2016 Feb 15;183(4):249-58. doi: 10.1093/aje/kwv242.