Biomarkers for Predicting Mortality

By Sarah Constantin

Biomarker

Adjusted HR for all-cause mortality

Troponin T (high)

3.5

GDF15 (high)

3.0

Frailty index

2.9

Zhang methylation score

2.6

NT-proBNP (high)

2.3

ST2 (high)

2.1

Self-reported health

2.0

Homocysteine (high)

2.0

IGFBP1 (high)

2.0

Vitamin D (low)

1.9

YKL-40 (high)

1.8

Albumin (low)

1.8

Klotho (low)

1.8

IL-6 (high)

1.8

Grip strength (low)

1.7

Magnesium (low)

1.6

Fibrinogen (high)

1.6

Neopterin (high)

1.6

CRP (high)

1.6

Cortisol (high)

1.5

Glucose (high)

1.5

DHEA (low)

1.5 (in men)

Iron (low)

1.5

Copper (high)

1.5

BDNF (low)

1.4

Testosterone (low)

1.4 (in men)

Horvath methylation score

1.4

Cholesterol (high)

1.4

Insulin (high)

1.4

Hannum methylation score

1.3

Osteoprotegerin (high)

1.3

Vitamin C (low)

1.3

GGT (high)

1.3

mtDNA

1.3

Adiponectin (high)

1.3

TNF-alpha (high)

1.3

Carotenoids (low)

1.3

Uric acid (high)

1.2

Resistin (high)

1.2

Parathyroid hormone (high)

1.2

Endothelin-1 (high)

1.1

This is an overview and rough effect-size scoring of biomarkers associated with all-cause mortality in observational studies drawn from general populations (i.e. not in patients diagnosed with a disease.)

The hazard ratio numbers in the chart are calculated by averaging the hazard ratios in the studies cited below, weighted by study size. Hazard ratios measure the relative risk of all-cause mortality in the “top” vs. “bottom” bin (tertiles, quartiles, etc) of the biomarker.  These averaged numbers should be taken with a grain of salt, because they’re aggregating the results of studies that aren’t strictly comparable; I’ve freely averaged hazard ratios between studies that used different binning formats, or different study populations (differing by country, age, gender, etc) or different follow-up period lengths, or different adjustment procedures (all hazard ratios are adjusted for age and sex, but many are additionally adjusted for other risk factors, like BMI or cholesterol.)  This isn’t intended to be a true meta-analysis, and the rank-ordering of the biomarkers by effect size may not be exact.

The purpose here is to illustrate and summarize what sorts of biomarkers that predict mortality have been observed so far, and to notice some patterns.

First of all, “clinical” rather than biochemical predictors do quite well.

People’s self-assessments of their own health are highly predictive of their mortality risk.  A single measurement of grip strength isn’t far behind. A simple frailty index consisting of 3 criteria (recent weight loss, difficulty standing, self-reported energy levels) does even better.  This is roughly what I’d have predicted; with few exceptions, the best “biomarker of aging” we have is direct observation of the subject’s state of overall health.

The Horvath and Hannum methylation “clocks” (patterns of methylation abnormalities associated with chronological age) don’t have particularly big impacts on mortality risk compared to frailty and self-reported health. The Zhang clock, which came out in 2017, looks quite a bit better at predicting mortality. That’s to be expected, since it’s a model trained on mortality rates, not ages.  (In my table I ignored the paper where the Zhang clock is tested on the dataset used to train it, which had an even larger hazard ratio but seemed like an overfitting risk.)  It remains to be seen if other researchers will replicate the Zhang clock.

There are some individual biomarkers that also seem to actually have comparable or larger effects on mortality risk than self-reported health or frailty.

Several are cardiac stress markers.  Troponin T is a protein involved in muscle contractions and elevated during heart attacks.  ST2, the receptor for the cardioprotective cytokine IL-33, is a cardiac biomarker that signals fibrosis from heart failure. (High levels of circulating ST2 in the blood bind to IL-33 and prevent it from doing its job in the heart.)  NT-proBNP is a prohormone secreted by the heart muscle to reduce blood pressure and cardiac output; it is elevated in heart failure.

Others seem to be generalized stress responses.  GDF15 is an inflammatory cytokine which is upregulated during injury to organs and increases with age.  YKL-40 is a glycoprotein which is secreted in response to inflammation, fibrosis, and cancer. IL-6 is an inflammatory cytokine, nicknamed the “gerontologist’s cytokine”, which is involved in inflammatory and stress responses and is associated with many age-related diseases.

Still others are involved in nutrient sensing.  IGFBP1 is the binding protein for IGF-1, a key protein in the insulin-signaling/nutrient-sensing pathway.  It prevents IGF-1 from taking glucose out of the bloodstream and into tissues to be used for growth; that is, IGFBP1 is anti-proliferative.  It increases with age, and high levels are associated with mortality. Klotho, on the other hand, is an inhibitor of the insulin-signaling pathway that decreases with age, and low levels are associated with age-related diseases and mortality.

Homocysteine is an amino acid variant; in high concentrations, it damages cells, leading to blood clots, atherosclerosis, and dementia. Homocysteine levels increase with age and can be elevated by B vitamin deficiencies.

Vitamin D production declines with age as a result of impaired renal function; low vitamin D increases the risk of fractures and falls.

Albumin is a protein that regulates blood volume; serum albumin declines with age as a result of impaired liver function and reduced protein intake.

Most of these markers seem more likely to be warning signs of aging processes than viable targets for anti-aging drugs, but they could be useful for more quickly predicting whether interventions are having anti-aging effects on an organism.  Though, as always, when you use a proxy metric without knowing the mechanism, you can’t be sure that the causality goes the right way; for all you know, the intervention is just directly altering the biomarker but not touching the progression of age-related disease.  This is why it’s good to observe that measures of frailty and physical performance are some of the best predictors of mortality; even if we don’t have the time for a long-term study on mortality, an intervention that’s shown to improve frailty is definitely valuable for the quality of life of the elderly, while we can’t have that same certainty about an intervention that only affects the concentration of some molecule in the blood.

Additionally, some biomarkers for mortality, like Klotho, do seem to have direct effects on aging and lifespan -- mice that overexpress Klotho live longer, and a recently founded startup is trying to develop a version of the protein as a treatment for chronic kidney disease.

Biomarkers

Adiponectin

In 4046 men aged 60-79, top-third adiponectin levels were associated with 1.55x adjusted risk of all-cause mortality.[1]

In 3263 participants from the Dallas Heart Study, Q4 vs Q1 adiponectin levels were associated with 2.27x the risk of all-cause mortality.[2]

In 3272 adults over 65 without heart disease from the Cardiovascular Health Study, adiponectin was positively correlated with age, and its relationship with all-cause mortality was U-shaped. Adiponectin above median was associated with a hazard rate for all-cause mortality of 1.19.[3]

In 2454 patients aged 50-75 in the Hoorn Study, high adiponectin did not have a significantly elevated hazard rate for all-cause mortality.[4]

In 2020 Japanese subjects, high-molecular weight adiponectin levels (top vs. bottom quartile) was associated with a 1.92x adjusted relative risk for all-cause mortality.[5]

Albumin

In a prospective study of 4116 men and women over 70, low albumin was associated with a 1.9x relative risk of all-cause mortality in men, and a 3.7x relative risk in women, after adjusting for age, race, chronic conditions, and disability status.  Unadjusted, those relative risks are 4.6 and 10.0 respectively.[6]

In the Estonian Biobank (n=9842) and a cohort from Finland (n=7503) adjusted relative risks of all-cause mortality were elevated due to the following biomarkers: alpha-1 acid glycoprotein (RR = 1.67),low albumin  (RR = 1.42), very low density LDL particle size (RR = 0.69) and citrate (1.33). Albumin was the strongest predictor of all-cause mortality, with p<10^(-25).[7]

In the Framingham Heart Study, in women but not men (2163 subjects), the top tertile of albumin is associated with 1.59x risk of all-cause mortality (2343 subjects).[8]

In the Longitudinal Aging Study Amsterdam, 713 participants, no association between albumin and all-cause mortality.[9]

In the British Regional Heart Study, 7735 middle-aged men, bottom vs. top quartile of albumin level was associated with a 2.16x increase in all-cause mortality.[10]

BDNF

In 188 85-year-old Danes, women (n=106) but not men (n=65) had a RR of 2.2 for bottom-tertile vs. top-tertile BDNF.[11]

In 3687 individuals, all-cause mortality in the bottom quartile of BDNF was 1.4x the mortality in the top quartile, p<0.0001.[12]



Carotenoids

Being in the lowest vs. highest tertile of carotenoid levels was associated with a 1.23x risk of death among 1043 adults over 65.[13]

Low plasma carotene levels were associated with a 1.27x adjusted risk of all-cause mortality in a study of 1168 elderly men & women.[14]



Cholesterol

High vs. low cholesterol levels in a cohort of 268,941 men were associated with 1.31-1.41x higher mortality rates.[15]

In 9216 Japanese participants over 30, the adjusted hazard ratio for all-cause mortality from being in the top out of 7 brackets for cholesterol was 1.36.[16]

Copper

In a cohort of 4035 men age 30-60, high copper levels were associated with a relative risk of all-cause mortality of 1.5, and low magnesium was associated with a relative risk of 1.67.[17]

In the ilSIRENTE study of 346 subjects, the adjusted hazard ratio for all-cause mortality for the top vs. bottom tertile of copper was 1.2.[18]

Cortisol

In 861 participants age 65+, from the InCHIANTI study, the top tertile of urinary cortisol had a relative risk of all-cause mortality compared to the bottom tertile of 5x.[19]

In 4255 US Army Vietnam veterans, cortisol was associated with all-cause mortality, with a hazard ratio of 1.71.[20]

In 5297 women from the Copenhagen City Heart Study, there was no elevated all-cause mortality risk associated with higher cortisol levels.[21]

In 4047 civil servants from the Whitehall II study, bedtime cortisol was associated with increased risk of all-cause mortality (1.33) but not morning cortisol.[22]

CRP

Top-quintile CRP levels had a 2.32x RR for all-cause mortality (p < 0.0001) in a study of 1395 men.[23]

In 675 elderly people over age 70, top-quartile  CRP was associated with a 1.7x adjusted risk of all-cause mortality.[24]

In 7015 participants from the Hordaland Health Study, top-quartile vs. bottom-quartile CRP adjusted RR was 1.49.[25]



In 10,388 Danish white people, high vs. low CRP levels were associated with an adjusted RR of 2 for all-cause mortality.[26]

In 11,193 participants over age 54, hazard ratios for CRP in the top fifth vs bottom fifth was associated with a 1.61 adjusted RR for all-cause mortality.  [27]

In 16,850 men & women aged 40-79 in the EPIC-Norfolk study there was a significantly elevated adjusted RR for all-cause mortality in the top quintile of CRP, at 1.2.[28]



Cysteine

In 12595 men and women ages 40-42 , and 4766 men and women ages 65-67, there was no association between cysteine and mortality.[29]

DHEA

In a study of 2644 Swedish men over age 69, low DHEA levels (bottom quartile) were associated with a 1.54 relative risk of all-cause mortality, after adjusting for age, BMI, CRP, and other cardiovascular risk factors.[30]

In 242 men aged 50-75, DHEA was not significantly associated with all-cause mortality, though it was associated with cardiovascular mortality.[31]

Endothelin-1

In 1440 healthy subjects, plasma endothelin was a predictor of all-cause mortality (RR = 1.11)[32]



Fibrinogen

Top quintile vs. bottom quintile for fibrinogen has an adjusted RR of 2.59 and 2.20 for men and women respectively, for all-cause mortality, in the Scottish Heart Health Study of 9955 subjects.[33]

In 610 Swedish men, after adjusting for smoking & other risk factors, the relative risk of all-cause mortality from being in the top third of fibrinogen was 2.6.[34]

In 16,850 men & women aged 40-79 in the EPIC-Norfolk study, men (8334) but not women (10,252) had a significantly elevated adjusted RR for all-cause mortality in the top quintile of fibrinogen, at 1.34.[35]

Frailty

In a multicenter study, the European Male Aging Study, of 2929 men, the adjusted hazard ratio for all-cause mortality for the frailty index for the top 18% vs. the bottom 60% was 4.00.[36]

In a cohort of 1851 subjects, the Zhang methylation score was associated with a hazard ratio of all-cause mortality per standard deviation of 1.62, so 2.62 for top 15% vs. bottom 15%, while the Horvath clock had an HR of 1.16 per standard deviation, and the frailty index had an HR of 1.42 per standard deviation, or 2.02 for top 15% vs. bottom 15%.[37]

In 3132 older men, the hazard ratio of “frail” (top 13% in frailty score according to the SOF index) vs. “robust” (bottom 44%) was 2.53.  The hazard ratio for the top 14% vs. bottom 32% for the CHS index was 3.51.[38]

In 6701 older women, the odds ratio for all-cause mortality among frail women by the CHS standard (top 17% vs. bottom 37%) was 2.75; for the SOF index (top 16% vs. bottom 47%) was 2.37.[39]

GDF15

In 876 Swedish men, age 35-80, serum GDF15 levels predicted all-cause mortality with an adjusted odds ratio of 3.38, p<0.0001.’[40]

In 940 subjects in the Uppsala Longitudinal Study of Adult Men, the top quartile of GDF-15 was associated with a 2.19x risk of all-cause mortality.[41]

In the Dallas Heart Study of 3219 people ages 30-65, elevated GDF15 was associated with a hazard ratio of all-cause mortality of 3.5, p < 0.0001.[42]

In 1391 participants from the Rancho Bernardo study, top-quartile GDF-15 had a hazard ratio of all-cause mortality of 2.25, p<0.0001.  GDF15 levels predicted both cardiovascular and non-cardiovascular mortality.[43]

Glucose

Top-quartile glucose in 2419 non-diabetics over 60 was associated with all-cause mortality with adjusted RR 1.49, only significant for women.[44]

In 1160 middle-aged nondiabetic men, high glucose levels were associated with an adjusted RR of all-cause mortality of 1.5.[45]

In the Whitehall Study (10,025), the Paris Prospective Study (6629), and the Helsinki Policemen Study (631), men had an adjusted RR of all-cause mortality of 1.6 for elevated blood glucose.[46]

In 10,026 nondiabetic Australians, high glucose was associated with a 1.2x RR of all-cause mortality.[47]

GGT

In a prospective study of 7613 British men,  highest-quintile gamma-glutamyltransferase (GGT) levels had a relative risk of 1.22 for all-cause mortality.[48]



In a study of 8043 male German construction workers age 30-60, high GGT levels were associated with a 1.44 RR of all-cause mortality. (p <0.001)[49]

Grip Strength

In a meta-analysis comprising 14 studies and 53,476 participants, top quarter vs. bottom quarter in grip strength was associated with a hazard ratio of all-cause mortality of 1.67 (p < 0.001).[50]

Homocysteine

In 1933 subjects over age 70 from the Framingham study, top-quartile homocysteine levels were associated with a relative risk of all-cause mortality of 2.18.  The effects after adjustment for age, sex, blood pressure, diabetes, smoking, total cholesterol, and HDL levels was 1.54 for all-cause mortality.[51]

Adjusted hazard ratio of 1.22 per 1 std of homocysteine for all-cause mortality in 5000 French subjects.[52]

12 studies, 23,623 subjects, highest vs. lowest category of homocysteine levels had an adjusted RR of mortality of 1.93.[53]

In 853 people over age 75, top-third vs. bottom-third homocysteine levels had a relative risk of all-cause mortality of 2.20.[54]

In 4248 men over 70, high homocysteine was associated with higher all-cause mortality (1.25 RR) after adjusting for frailty & other covariates.[55]

In the Hordaland study of 2127 men and 2629 women, top quintile vs. bottom quintile homocysteine level was associated with 3.6x all-cause mortality risk.[56]



IGF-1, IGFBP1

In a study of 715 older adults, after adjusting for other cardiovascular risk markers, the hazard ratio for all-cause mortality between the top quintile and bottom quintile of IGFBP-1 was 3.11, and for IGF was 1.4.  Age-adjusted but without accounting for other CVD risk factors, the effect was non-significant for both.[57]



In 576 individuals, top-quartile vs. all other IGF-1 levels were associated with 1.52x RR of mortality.[58]

Of 525 subjects over age 72, mortality was associated with an adjusted RR of 1.27 for TNF-alpha and 1.3 for IL-6 but not with IGF-1, where mortality was associated with an 0.70 RR.[59]

In the Health n Men study of 3983 men over 70, IGFBP1 (top vs. bottom quartile) was associated with a hazard ratio of 1.98 for all-cause mortality, but IGF was not associated.)[60]

In the Health, Aging, and Body Composition study, of 625 men and women over 70, top vs. bottom quartile IGFBP1 was associated with a HR of 1.8 of all-cause mortality.[61]

In 997 people over 77, from the Cardiovascular Health All-Stars Study, top-quartile vs. bottom-quartile IGFBP1 was associated with an HR of 1.96 for all-cause mortality, while IGF-1 had no significant association[62].

IL-6

Of 525 subjects over age 72, mortality was associated with an adjusted RR of 1.27 for TNF-alpha and 1.3 for IL-6 but not with IGF-1, where mortality was associated with an 0.70 RR.[63]

In 675 elderly people over age 70, top-quartile IL-6 levels were associated with a 2.1x adjusted risk of all-cause mortality.[64]

Insulin

In a study of 970 Finnish policemen, high insulin (top quintile) was associated with a relative risk of 1.51 of all-cause mortality; after adjustment, it was 1.37.[65]

Iron

In a cohort of 3936 people over 71, the RR for iron in the bottom quartile vs. top quartile was 1.61 for men, 1.39 for women. Adjusted for age, race, education, creatinine, albumin, lipids, iron supplementation, smoking, alcohol, blood pressure, BMI, and chronic conditions.[66]

Klotho

In 804 adults in Tuscany, participants in the lowest tertile of klotho levels had 1.78x the risk of death of the highest tertile, after adjusting for other risk factors.[67]

Magnesium

In a cohort of 4035 men age 30-60, high copper levels were associated with a relative risk of all-cause mortality of 1.5, and low magnesium was associated with a relative risk of 1.67.[68]

In the SHIP study including 3910 subjects age 20-79, low magnesium levels were associated with an adjusted relative risk of all-cause mortality of 1.5.[69]

Methylation Signatures

The adjusted HR for Horvath methylation age - chronological age in terms of all-cause mortality was 1.09 per standard deviation, p < 0.0001, or 1.19 HR for top 15% vs. bottom 15%.[70]

For the Hannum methylation difference, it was 1.16 per standard deviation, or 1.35 HR for top 15% vs. bottom 15%. This comes from four cohorts, totaling 3690 subjects.[71]

In a cohort of 1863 older people, hazard ratio for the Horvath methylation score per 5 years was 1.22 and for the Hannum methylation score was 1.03, or a top 15% vs. bottom 15% hazard ratio of 1.82 for Horvath score and 1.09 for the Hannum score.[72]

In a cohort of 998 subjects, all-cause mortality is 7.36x higher in the top 13% vs.bottom 20% (ESTHER study) and 3.19x higher in the top half vs. bottom half (KORA study) of 1728 participants.  No overlap with previously reported CpG sites.[73]



In Scottish cohorts comprising 1344 individuals, the hazard ratio for all-cause mortality associated with one standard deviation in Hannum methylation age was 1.24 (so top 15% vs bottom 15% was 1.54).[74]

In a cohort of 1851 subjects, the Zhang methylation score was associated with a hazard ratio of all-cause mortality per standard deviation of 1.62, so 2.62 for top 15% vs. bottom 15%, while the Horvath clock had an HR of 1.16 per standard deviation, and the frailty index had an HR of 1.42 per standard deviation, or 2.02 for top 15% vs. bottom 15%.[75]

mtDNA

In the Cardiovascular Health Study (CHS), 4892 participants, and the Atherosclerosis Risk In Communities (ARIC) study, 11,509 participants, mtDNA copy number (the amount of mitochondrial DNA in whole blood) declined with age, was higher in women than men, was associated with frailty (OR = 0.91), and the bottom vs. top quintile for mtDNA had an all-cause mortality hazard ratio of 1.32 after adjusting for other cardiovascular risk factors as well as age & sex.[76]

Neopterin

In 7015 participants from the Hordaland Health Study, top-quartile neopterin vs. bottom-quartile was associated with a 1.54 adjusted RR of all-cause mortality.  Kynurenine-tryptophan ratio adjusted RR was 1.6. CRP adjusted RR was 1.49.[77]

In 2312 subjects in the Ludwigshafen Risk & Cardiovascular Health Study, top-quartile neopterin was associated with an adjusted all-cause mortality risk of 1.61.[78]

NT-proBNP

In 8383 subjects, top vs. bottom quintile of NT-proBNP was associated with an adjusted RR of 1.27 for all-cause mortality.[79]

In 11,193 participants over age 54, hazard ratios for NT-proBNP in the top fifth vs bottom fifth was associated with a 3.05 adjusted RR for all-cause mortality.  (p < 0.0001)[80]

In 957 older adults in the Rancho Bernardo Study, adjusted HR for elevated NT-proBNP was 2.06.[81]

Osteocalcin

In 3542 older men, osteocalcin has a U-shaped distribution: 1.5x risk of mortality in top vs. 2nd quartile, 1.35x risk of mortality in bottom vs. 2nd quartile.[82]

Osteoprotegerin

Osteoprogerin levels were associated with a 1.4x age-adjusted odds ratio in all-cause mortality in 490 white women older than 65.[83]

In the Tromso study of 6265 subjects, osteoprotegerin levels were associated with a 1.34x risk of all-cause mortality.[84]

Parathyroid Hormone

In 633 subjects from the Hoorn study, top-quartile parathyroid hormone was associated with a higher adjusted risk of all-cause mortality: HR = 1.98.[85]

In 2312 participants in the Cardiovascular Health Study, parathyroid hormone was not associated with elevated all-cause mortality.[86]

In 1433 older men, top-quartile PTH levels were associated with a 1.32x risk of all-cause mortality.[87]

In a meta-analysis of 31,616 subjects, elevated PTH increased the risk of all-cause mortality with HR 1.19.[88]

Resistin

In a metastudy of 4016 subjects, the adjusted RR for each standard deviation of resistin levels for all-cause mortality is 1.24.[89]

Selenium

In 13,887 participants in the NHANES survey, the adjusted hazard ratio for all-cause mortality between the top and bottom tertile of selenium was 0.83.[90]

In 1042 men and women over 64 from the InCHIANTI study, adults in the lowest vs. highest quartile had a hazard ratio for adjusted mortality of 1.6.[91]

Self-reported health

Adjusted HR for all-cause mortality between top quintile & bottom quintile of self-reported health was 2.0, in the SHIP study of 4308 subjects.

sFas

In 238 nonagenarians, sFas was not independently associated with all-cause mortality.[92]



ST2

ST2, part of the IL-1 receptor family, in the top quartile is associated with adjusted all-cause mortality ratio of 2.1 (p < 0.0001), in the Dallas Heart Study of 3294 subjects.[93]

Uric Acid

Hazard ratios for hyperuricemia are associated with all-cause mortality in a cohort of 90,393 Chinese adults: hazard ratio 1.16 (p<0.001)[94]

Elevated serum uric acid increased the risk of all-cause mortality in a meta-analysis comprising 172,123 individuals; RR = 1.23[95]



Testosterone

In a study of 790 men aged 50-91, men in the bottom quartile of testosterone levels had a relative risk of all-cause mortality of 1.4, adjusted for age, adiposity, and lifestyle.  Adjusting for other risk factors had minimal effect on the relative risk.[96]

Troponin T

In 3456 individuals aged 30-65 in the Dallas Heart Study, cardiac troponin T in the top vs. bottom quartile was associated with a 2.8 adjusted RR for all-cause mortality.[97]

In 11,193 participants over age 54, hazard ratios for troponin T in the top fifth vs bottom fifth was associated with a 3.42 adjusted RR for all-cause mortality. [98]

In the ARIC study of 9698 participants over 50, elevated troponin T levels were associated with a hazard ratio of total mortality of 3.96.[99]

In 804 men and 618 women from the ActiFE study in Ulm, elevated troponin T was associated with a hazard ratio of all-cause mortality of 2.97 in women and 1.73 in men.[100]

Vitamin C

In 8453 Americans over 30 from the NHANES study, bottom-tertile vitamin C levels were associated with a 1.33x RR of all-cause mortality.[101]



Vitamin D

In a meta-study of 32 studies of the association of serum vitamin D levels with all-cause mortality, the hazard ratio was 1.9 (p<0.001). The studies adjusted for age and other variables.[102]

3258 middle-aged male and female subjects had a 2.04x hazard ratio in all-cause mortality between the bottom two quartiles and top two quartiles in vitamin D levels.[103]

In 7161 subjects in the Tromso study, among non-smokers, there was a significant 1.32 relative risk of all-cause mortality in the bottom quartile of vitamin D levels compared to the top quartile. The effect was not significant for smokers.[104]

YKL-40

In 115 octogenerians, high YKL-40 levels (top third vs. bottom third) were associated with an adjusted relative risk of 2.20 of all-cause mortality.[105]

In the Copenhagen City Heart Study of 8899 study participants, aged 20-95, hazard ratio for all-cause mortality was 1.9 for individuals in the top 5% of YKL-40 vs. the bottom 33%. Trend, p<0.0001.[106]

In 1407 patients >40 admitted to the Copenhagen hospital and healthy subjects from the Danish Heart Study, top-quartile levels of YKL-40 were associated with a 1.5x adjusted risk of all-cause mortality.[107]

Zinc

Zinc is not associated independently with all-cause mortality.[108]




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