How mRNA and DNA vaccines could soon treat cancers, HIV, autoimmune disorders and genetic diseases

The idea of using genetic material to produce an immune response has opened up a world of research and potential medical uses far out of reach of traditional vaccines. Deborah Fuller is a microbiologist at the University of Washington who has been studying genetic vaccines for more than 20 years. We spoke to her about the future of mRNA vaccines.

Below are excerpts from that conversation which have been edited for length and clarity.

This article is a repost which originally appeared on The Conversation
Deborah Fuller - January 6, 2022
Edited for content and readability - Images sourced from Pexels 

Our Takeaways:

  • Nucleic acid vaccines are based on the idea that DNA makes RNA and then RNA makes proteins.
  • These vaccines are effective at inducing a T cell response.
  • For cancer, the goal is to make your body better able to recognize the very specific neoantigens the cancer cell has produced and destroy it.
  • For autoimmune disorders, the vaccine would suppress the T Cells to keep the immune system from attacking myelin

How long have gene-based vaccines been in development?

This type of vaccine has been in the works for about 30 years. Nucleic acid vaccines are based on the idea that DNA makes RNA and then RNA makes proteins. For any given protein, once we know the genetic sequence or code, we can design an mRNA or DNA molecule that prompts a person’s cells to start making it.

When we first thought about this idea of putting a genetic code into somebody’s cells, we were studying both DNA and RNA. The mRNA vaccines did not work very well at first. They were unstable and they caused pretty strong immune responses that were not necessarily desirable. For a very long time DNA vaccines took the front seat, and the very first clinical trials were with a DNA vaccine.

But about seven or eight years ago, mRNA vaccines started to take the lead. Researchers solved a lot of the problems – notably the instability – and discovered new technologies to deliver mRNA into cells and ways of modifying the coding sequence to make the vaccines a lot more safe to use in humans.

Once those problems were solved, the technology was really poised to become a revolutionary tool for medicine.

What makes nucleic acid vaccines different from traditional vaccines?

Most vaccines induce antibody responses. Antibodies are the primary immune mechanism that blocks infections. As we began to study nucleic acid vaccines, we discovered that because these vaccines are expressed within our cells, they were also very effective at inducing a T cell response. This discovery really prompted additional thinking about how researchers could use nucleic acid vaccines not just for infectious diseases, but also for immunotherapy to treat cancers and chronic infectious diseases – like HIV, hepatitis B and herpes – as well as autoimmune disorders and even for gene therapy.

How can a vaccine treat cancers or chronic infectious diseases?

T cell responses are very important for identifying cells infected with chronic diseases and aberrant cancer cells. They also play a big role in eliminating these cells from the body.

When a cell becomes cancerous, it starts producing neoantigens. In normal cases, the immune system detects these neoantigens, recognizes that something’s wrong with the cell and eliminates it. The reason some people get tumors is that their immune system isn’t quite capable of eliminating the tumor cells, so the cells propagate.

With an mRNA or DNA vaccine, the goal is to make your body better able to recognize the very specific neoantigens the cancer cell has produced. If your immune system can recognize and see those better, it will attack the cancer cells and eliminate them from the body.

This same strategy can be applied to the elimination of chronic infections like HIV, hepatitis B and herpes. These viruses infect the human body and stay in the body forever unless the immune system eliminates them. Similar to the way nucleic acid vaccines can train the immune system to eliminate cancer cells, they can be used to train our immune cells to recognize and eliminate chronically infected cells.

What is the status of these vaccines?

Some of the very first clinical trials of nucleic acid vaccines happened in the 1990s and were for cancer, particularly for melanoma.

Today, there are a number of ongoing mRNA clinical trials for the treatment of melanoma, prostate cancer, ovarian cancer, breast cancer, leukemia, glioblastoma and others, and there have been some promising outcomes. Moderna recently announced promising results with its phase 1 trial using mRNA to treat solid tumors and lymphoma

There are also a lot of ongoing trials looking at cancer DNA vaccines, because DNA vaccines are particularly effective in inducing T cell responses. A company called Inovio recently demonstrated a significant impact on cervical cancer caused by human papilloma virus in women using a DNA vaccine.

Can nucleic acid vaccines treat autoimmune disorders?

Autoimmune disorders occur when a person’s immune cells are actually attacking a part of the person’s own body. An example of this is multiple sclerosis. If you have multiple sclerosis, your own immune cells are attacking myelin, a protein that coats the nerve cells in your muscles.

The way to eliminate an autoimmune disorder is to modulate your immune cells to prevent them from attacking your own proteins. In contrast to vaccines, whose goal is to stimulate the immune system to better recognize something, treatment for autoimmune diseases seeks to dampen the immune system so that it stops attacking something it shouldn’t. Recently, researchers created an mRNA vaccine encoding a myelin protein with slightly tweaked genetic instructions to prevent it from stimulating immune responses. Instead of activating normal T cells that increase immune responses, the vaccine caused the body to produce T regulatory cells that specifically suppressed only the T cells that were attacking myelin.

Any other applications of the new vaccine technology?

The last application is actually one of the very first things that researchers thought about using DNA and mRNA vaccines for: gene therapy. Some people are born missing certain genes. The goal with gene therapy is to supply cells with the missing instructions they need to produce an important protein.

A great example of this is cystic fibrosis, a genetic disease caused by mutations in a single gene. Using DNA or an mRNA vaccine, researchers are investigating the feasibility of essentially replacing the missing gene and allowing someone’s body to transiently produce the missing protein. Once the protein is present, the symptoms could disappear, at least temporarily. The mRNA would not persist very long in the human body, nor would it integrate into people’s genomes or change the genome in any way. So additional doses would be needed as the effect wore off.

Research has shown that this concept is feasible, but it still needs some work.

Reference Ranges for Testosterone in Men Generated Using Liquid Chromatography Tandem Mass Spectrometry in a Community-Based Sample of Healthy Nonobese Young Men in the Framingham Heart Study and Applied to Three Geographically Distinct Cohorts

Reference Ranges for Testosterone in Men Generated Using Liquid Chromatography Tandem Mass Spectrometry in a Community-Based Sample of Healthy Nonobese Young Men in the Framingham Heart Study and Applied to Three Geographically Distinct Cohorts

Shalender Bhasin, Michael Pencina, Guneet Kaur Jasuja, Thomas G. Travison, Andrea Coviello, Eric Orwoll,* Patty Y. Wang,* Carrie Nielson,* Frederick Wu,* Abdelouahid Tajar,* Fernand Labrie, Hubert Vesper, Anqi Zhang, Jagadish Ulloor, Ravinder Singh, Ralph D’Agostino, and Ramachandran S. Vasan

Recommended by Pegasus

This article is a repost which originally appeared on PUBMED


Reference ranges are essential for partitioning testosterone levels into low or normal and making the diagnosis of androgen deficiency. We established reference ranges for total testosterone (TT) and free testosterone (FT) in a community-based sample of men.


TT was measured using liquid chromatography tandem mass spectrometry in nonobese healthy men, 19–40 yr old, in the Framingham Heart Study Generation 3; FT was calculated. Values below the 2.5th percentile of reference sample were deemed low. We determined the association of low TT and FT with physical dysfunction, sexual symptoms [European Male Aging Study (EMAS) only], and diabetes mellitus in three cohorts: Framingham Heart Study generations 2 and 3, EMAS, and the Osteoporotic Fractures in Men Study.


In a reference sample of 456 men, mean (sd), median (quartile), and 2.5th percentile values were 723.8 (221.1), 698.7 (296.5), and 348.3 ng/dl for TT and 141. 8 (45.0), 134.0 (60.0), and 70.0 pg/ml for FT, respectively. In all three samples, men with low TT and FT were more likely to have slow walking speed, difficulty climbing stairs, or frailty and diabetes than those with normal levels. In EMAS, men with low TT and FT were more likely to report sexual symptoms than men with normal levels. Men with low TT and FT were more likely to have at least one of the following: sexual symptoms (EMAS only), physical dysfunction, or diabetes.


Reference ranges generated in a community-based sample of men provide a rational basis for categorizing testosterone levels as low or normal. Men with low TT or FT by these criteria had higher prevalence of physical dysfunction, sexual dysfunction, and diabetes. These reference limits should be validated prospectively in relation to incident outcomes and in randomized trials.

Androgen deficiency in men is a syndrome characterized by a constellation of symptoms and signs and low circulating testosterone levels (1). Thus, the diagnosis of androgen deficiency is predicated upon the determination of whether the circulating testosterone level is low or normal (1–3). Rigorously established reference ranges constitute the essential basis for identifying whether the circulating levels of an analyte, such as testosterone, are normal or low. The reference ranges for testosterone have been derived previously mostly from small convenience samples (2–9) or from hospital or clinic-based patients; these approaches are limited by their inherent selection bias, because patients seeking medical care are more likely to have a disease than individuals in the general population. Some recent efforts to generate reference ranges in community-dwelling men are notable; these studies included middle-aged and older men and used direct RIA (10), whose accuracy, particularly in the low range, has been questioned (3, 11, 12). In the absence of rigorously determined reference limits generated using reliable assays in community-based samples, the partitioning of total and free testosterone levels into normal or low values has been fraught with substantial risk of misclassification (2, 3, 13), relegating many healthy men to unnecessary risks of testosterone therapy and preventing others from receiving appropriate testosterone therapy because of a missed diagnosis.

We generated reference limits for total and free testosterone concentrations in a community-based sample of healthy young men in the Framingham Heart Study (FHS) third generation (Gen 3) cohort (14). Total testosterone was measured using liquid chromatography tandem mass spectrometry (LC-MS/MS), a method with high specificity, sensitivity, and accuracy (2, 3, 11–13). We applied these reference limits to three geographically distinct cohorts of community-dwelling men: FHS Gen 2 and 3 (14), the European Male Aging Study (EMAS) (15, 16), and the Osteoporotic Fractures in Men Study (MrOS) (17). We determined whether men in these three cohorts, deemed to have low total and free testosterone levels by the proposed reference limits, had a higher prevalence of physical dysfunction, sexual symptoms, and diabetes mellitus (DM), the three categories of conditions that have been associated most consistently with low testosterone levels (18–27). We used thresholds based on a healthy young reference sample (T-score approach) because in exploratory analyses, the T-score approach and age-adjusted thresholds (Z-score approach) yielded concordant results for most outcomes. Also, the spline plots of testosterone levels against outcomes in the FHS sample did not reveal clear inflection points at which the relationship between testosterone levels and outcomes changed abruptly. The T-score approach based on limits derived in a healthy young population has been favored historically for analytes that exhibit clinically meaningful age-related trends, such as estradiol and bone mineral density.

Materials and Methods

Study sample

In 1948, to identify risk factors for cardiovascular disease (CVD), the FHS recruited 5209 men and women between the ages of 30 and 62 from Framingham, MA, that constituted the original cohort. In 1971, the study enrolled a second-generation cohort (Gen 2), 5124 of the original participants’ adult children and their spouses. A third generation (4095 children of Gen 2, referred to as Gen 3) was recruited in 2002–2005 (14) to further understand how genetic factors relate to cardiovascular disease risk. The FHS design and methods have been described. The recruitment methods and the selection criteria for Gen 3 participants have been published (14) and are described briefly in the Supplemental Methods (published on The Endocrine Society’s Journals Online web site at Of the 1912 men who attended the first Gen 3 examination (2002–2005), 1893 had total testosterone measurements, 962 were 40 yr of age or younger among whom 456 men were free of cancer (self-report of physician diagnosis supported by medical records when available), CVD (occurrence of any of the following: myocardial infarction, sudden death, stroke, congestive heart failure, coronary angioplasty or coronary artery bypass surgery, claudication, or peripheral angioplasty), DM, hypertension, hypercholesterolemia, obesity, and smoking, and constituted the reference sample (Fig. 1). Cardiometabolic disorders have been associated with low testosterone levels; therefore, men with cardiometabolic disorders were excluded from the reference sample. The men who were receiving androgen deprivation therapy or had undergone orchiectomy for prostate cancer or were taking testosterone for hypogonadism were excluded.

An external file that holds a picture, illustration, etc.
Object name is zeg0081182520001.jpg

Fig. 1.

The STROBE diagram: selection of the FHS reference sample. Of the 1912 men who attended the first Gen 3 examination (2002–2005), 1893 had total testosterone measurements, 962 were 40 yr of age or younger, and 456 men were free of cancer, CVD, DM, hypertension, hypercholesterolemia, obesity, and smoking.

Application to EMAS, MrOS, and FHS broad samples

We assessed whether low total and free testosterone levels, defined as values below the 2.5th percentile of the reference sample, were associated with three categories of conditions that have been associated with low testosterone levels (18–27): physical dysfunction, sexual symptoms, and DM in the FHS broad sample (see below), the EMAS, and MrOS. The FHS broad sample was created by combining Gen 2 and Gen 3 samples (Supplemental Fig. 1A). The Gen 2 examination 7 (1998–2002) was attended by 1625 men. Exclusion of men with prostate cancer undergoing androgen deprivation therapy (n = 8) or testosterone therapy and those with missing testosterone data (n = 158) resulted in a sample of 1459 for Gen 2. This combined sample of 3352 men (1459 men in Gen 2 plus 1893 men in Gen 3) constituted the FHS broad sample. The walking speed data were available in 797 Gen 2 men who attended exam 7 and had nonmissing testosterone data.

The EMAS recruited 3369 men, aged 40–79 yr, at eight European centers (15, 16): Manchester (UK), Leuven (Belgium), Malmö (Sweden), Tartu (Estonia), Lodz (Poland), Szeged (Hungary), Florence (Italy), and Santiago de Compostela (Spain). The men, randomly selected from the general population, were invited for study-related assessments, including an interviewer-assisted questionnaire, several performance measures, and a fasting blood test before 1000 h. One hundred fifty men were excluded because of known pituitary, testicular, or adrenal disease or use of medications that affect sex-steroid production or action yielding an analytic sample of 3219 men (Supplemental Fig. 1B).

MrOS, an observational study of the determinants of fracture in older men, recruited 5995 community-dwelling men at least 65 yr old at six U.S. centers (17). Of 5995 men who were recruited, total testosterone was measured on fasting, morning serum specimens in 1488 randomly selected men. Among these, 19 men were excluded for missing total testosterone data, and 95 were excluded because of the use of androgens or antiandrogens or reported orchiectomy as a treatment for prostate cancer, resulting in a final analytical sample of 1488 participants (Supplemental Fig. 1C).

Physical function measures (walking speed and self-reported mobility limitation in subsets of FHS, walking speed and frailty in MrOS, and walking speed and self-reported difficulty walking or climbing stairs in EMAS) and diabetes were available in all three cohorts; data on sexual symptoms were available only in EMAS.

Ascertainment of outcomes in the FHS

The self-reported mobility limitation in FHS was determined using a modified Rosow-Breslau questionnaire (28), which has been shown to have high test-retest reliability in other large population-based studies (19, 29, 30). Participants were asked whether they were able to 1) do heavy work around the house, like shovel snow or wash windows, walls, or floors without help; 2) walk half a mile without help (about four to six blocks); and 3) walk up and down one flight of stairs. At this exam, the last item was asked as part of the Katz Activities of Daily Living scale with the following directive: during the course of a normal day, can you walk up and down one flight of stairs independently or do you need human assistance or the use of a device? Response choices included 1) no help needed, independent; 2) uses device, independent; 3) human assistance needed, minimally dependent; 4) dependent; and 5) do not do during a normal day. If the participant reported independence, he was considered able to perform the mobility task (19). A participant was considered to have a mobility limitation if he reported an inability to do one or more of the three items on the scale (19, 28).

Usual walking speed was assessed by asking the participants to walk at their usual pace over a 4-m course at an ancillary study to examination 7 in Gen 2 (19). Participants were allowed to use walking aids if necessary, but not the assistance of another person. For individuals who did not attempt or complete the walk, the value was set to the maximum value obtained by any individual.

DM was defined as a fasting blood glucose of at least 126 mg/dl and/or the use of diabetes medication. Hypertension was defined as systolic blood pressure of at least 140 or diastolic blood pressure at least 90 mm Hg and/or the use of hypertension treatment. Hypercholesterolemia was defined by total cholesterol of at least 240 mg/dl or use of cholesterol-lowering medication. Obesity was defined as body mass index of at least 30 kg/m2.

Ascertainment of outcomes in the MrOS

For the measurement of walking speed, the participants were instructed to walk at a comfortable pace over a path of 6 m and completed two consecutively trials without a rest (31). Walking speed was calculated in meters per second using the time to complete two trials. The walking attempts were completed consecutively without a rest between attempts. Slow walking speed was defined if a participant was unable to complete the walk or scored in the slowest 20th percentile based on height-specific thresholds (0.99 m/sec for height ≤174.35 cm, 1.06 m/sec for height >174.35 cm).

Frailty was defined using modified criteria from the Cardiovascular Health Study and previous analyses in MrOS (32, 33). The Cardiovascular Health Study definition uses five components to define the presence of frailty: shrinking/sarcopenia, weakness, slowness, low activity level, and exhaustion (33). Participants with at least three components were defined as frail.

Diabetes was defined by fasting glucose above 126 mg/dl, use of oral hypoglycemic medications or insulin, or self-report of a physician’s diagnosis.

Ascertainment of outcomes in EMAS

The operational definitions of conditions and symptoms in the EMAS are shown in Supplemental Table 1.

Hormone measurements

FHS samples were obtained in the morning, after an overnight fast of approximately 10 h, typically between 0730 and 0830 h. The samples were aliquoted, frozen immediately, and stored at −80 C until the time of assay. The stability of FHS samples in storage has been evaluated previously by measuring the concentrations of cholesterol, high-density lipoprotein cholesterol and triglycerides in samples in the low, mid, and high range before freezing and storage at examination cycle 5 in 1991–1995 with repeated measurement in 2007, after storage at −80 C (34). The concentrations of these analytes were unchanged over a 15-yr period of storage at −80 C in the FHS repository using processes that are similar to those used for the collection and storage of samples included in the analyses reported here with correlation coefficients of measurements in 1991–1995 with repeated measurement in 2007 of 0.985, 0.997, and 0.948, respectively.

We measured total testosterone in the FHS Gen 2 and 3 samples using the same LC-MS/MS assay (19, 35). The functional limit of detection, defined as the lowest concentration, detected with less than 20% coefficient of variation (CV), was 2 ng/dl; no sample was outside the linear range of 2–2000 ng/dl. The recovery was calculated by adding known amounts of testosterone to charcoal-stripped serum and analyzing them by LC-MS/MS. The correlation between the amount added and the amount measured by LC-MS/MS was 0.998. The average recovery was 102 ± 3%. The cross-reactivity of dehydroepiandrosterone, dehydroepiandrosterone sulfate, and dihydrotestosterone, androstenedione, and estradiol in the testosterone assay was negligible at 10 times the circulating concentrations of these hormones. The interassay CV was 15.8% at 12.0 ng/dl, 10.6% at 23.5 ng/dl, 7.9% at 48.6 ng/dl, 7.7% at 241 ng/dl, 4.4% at 532 ng/dl, and 3.3% at 1016 ng/dl. As part of the Centers for Disease Control’s (CDC) Testosterone Assay Harmonization Initiative, quality control samples provided by the CDC were run every 3 months; the CV in quality control samples with testosterone concentrations in the 100- to 1000-ng/dl range was consistently less than 6%. In addition, 28 serum samples from men and women with testosterone concentrations across the male and female range were measured in a blinded manner in the Boston University and Mayo laboratories. The Pearson correlation between values obtained in the two laboratories was higher than 0.99, and Bland-Altman plots revealed no significant differences between values obtained in the two laboratories.

Total testosterone levels in the EMAS (36) and MrOS (37) samples were measured using gas chromatography-MS/MS with sensitivities of 5 and 2.5 ng/dl, respectively. The assays used for measurement of testosterone in MrOS and EMAS have not been cross-calibrated by exchange of samples. In all cohorts, free testosterone was calculated using a published law-of-mass-action equation that uses an association constant estimated from a systematic review of published binding studies and an iterative numerical method (38). The intra- and interassay CV in the low, medium, and high pools were 4.3, 5.5, and 4.9% and 2.4, 8.1, and 2.5%, respectively.

SHBG levels were measured using a two-site immunofluorometric assay (DELFIA-Wallac, Inc., Turku, Finland) (19, 39). The interassay CV were 8.3, 7.9, and 10.9%, and intraassay CV were 7.3, 7.1, and 8.7%, respectively, in the low, medium, and high pools. The analytical sensitivity of the assays was 0.5 nmol/liter.

Statistical methods

By convention, the 2.5th percentile of the FHS reference sample defines the lower limit of the reference range (40–42); total or free testosterone concentrations below the 2.5th percentile value (total testosterone <348.3 ng/dl; free testosterone <70.0 pg/ml) were deemed low.

We determined the relationship of total and free testosterone with outcomes in three community-based samples. For these cross-sectional analyses, we related total and free testosterone levels (separate models for each) to prevalence of physical dysfunction, sexual symptoms, and diabetes (fasting glucose ≥126 mg/dl or on treatment) using multivariable logistic regression models adjusting for age and smoking. Furthermore, In the EMAS and MrOS, which were multicenter studies, the analyses were also adjusted for the study site. We did not adjust for comorbid conditions because some of the comorbid conditions (e.g. diabetes) were the dependent variables in these analyses. Testosterone was modeled as a binary variable (low vs. normal).

In exploratory analyses, we evaluated the Z-score approach, in which hormone levels were regressed on age and standardized residuals were used for continuous analysis. Low testosterone levels were established by ranking the residuals and taking the lowest 10% (or 5%) as the threshold. The T-score and Z-score approaches yielded directionally concordant results (Supplemental Table 2). Also, analyses of spline plots of testosterone levels against outcomes did not yield clear thresholds at which the relationship of testosterone and outcomes changed abruptly.

All analyses were performed using SAS version 9.1 (SAS Institute, Cary, NC), and statistical significance was based on type I error probability of 0.05. The statistical analyses in the EMAS data were conducted using Intercooled STATA version 9.2 (StataCorp, College Station, TX).


Subject characteristics

The STROBE (strengthening the reporting of observational studies in epidemiology) diagram (Fig. 1) illustrates the selection of reference sample of healthy men, 40 yr of age or younger, who were free of cancer, CVD, DM, obesity, hypertension, hypercholesterolemia, and smoking. The baseline characteristics of the samples are summarized in Tables 1 and ​and2.2. The men in the FHS broad sample were on average younger and had lower prevalence of CVD, diabetes, and cancer than those in the EMAS and MrOS samples (Table 2).

Table 1.

Characteristics of the FHS Gen 3 reference sample

All subjects (n = 1893) All subjects ≤40 yr (n = 962) Reference sample ≤40 yra (n = 456)
Age (yr) 40.3 (8.8) 33.3 (5.5) 32.7 (5.7)
    <30 224 (11.8%) 224 (23%) 125 (27.4%)
    30–39 650 (34.3%) 650 (67.6%) 297 (65.1%)
    40–49 726 (38.4%) 88b (9.2%) 34b (7.5%)
    50–59 274 (14.5%) NA NA
    ≥60 19 (1%) NA NA
Caucasian or White 1880 (99.3%) 956 (99.4%) 454 (99.6%)
Family income
    <$12,000 33 (1.8%) 17 (1.9%) 11 (2.6%)
    $12,000–$24,000 60 (3.3%) 39 (4.3%) 18 (4.3%)
    $25,000–$49,999 323 (18%) 192 (21.3%) 73 (17.3%)
    $50,000–$74,999 448 (24.9%) 220 (24.4%) 105 (24.8%)
    $75,000–$100,000 369 (20.5%) 184 (20.4%) 94 (22.2%)
    >$100,000 566 (31.5%) 249 (27.6%) 122 (28.8%)
Systolic BP (mm Hg) 120.8 (12.6) 118.5 (11) 115.5 (8.9)
Diastolic BP (mm Hg) 78.3 (9.3) 76.9 (9.4) 74.1 (7.6)
Hypertension treatment 194 (10.3%) 40 (4.2%) NA
Total cholesterol (mg/dl) 193 (37.2) 188.5 (39.5) 178.5 (30.2)
LDL cholesterol (mg/dl) 119.8 (31.6) 116.9 (31.9) 110.6 (27.4)
HDL cholesterol (mg/dl) 46.8 (12.4) 46.4 (12.0) 47.6 (11.8)
Triglycerides (mg/dl) 136.1 (109.7) 128 (102.4) 103.8 (72.3)
Cholesterol treatment 208 (11%) 45 (4.7%) NA
Glucose (mg/dl) 98.6 (17.8) 95.6 (14.1) 93.0 (6.8)
Diabetes treatment 42 (2.2%) 8 (1%) NA
Body mass index (kg/m2) 28.0 (4.7) 27.4 (4.6) 25.5 (2.7)
Cancer 27 (1.4%) 14 (1.5%) NA
Prevalent CVD 45 (2.4%) 7 (1%) NA
Diabetes 48 (2.5%) 8 (1%) NA
Obesity 493 (26%) 216 (22.5%) NA
Hypertension 416 (22%) 127 (13.2%) NA
Hypercholesterolemia 370 (19.6%) 119 (12.4%) NA
Smoker 347 (18.3%) 183 (19%) NA

Values are means (sd) or n (%); BP, Blood pressure; HDL, high-density lipoprotein; LDL, low-density lipoprotein; NA, not applicable.

aHealthy samples from subjects free of cancers, CVD, diabetes, obesity, hypertension, and hypercholesterolemia and who were nonsmokers.
bThese men are exactly 40 yr of age.

Table 2.

Characteristics of the participants in the three cohorts

Broad FHS sample (Gen 2 plus Gen 3) (n = 3352) EMAS (n = 3219) MrOS (n = 1488)
Age (yr) 49.4 (13.8) 59.7 (11.0) 73.7 (5.8)
    <30 224 (6.7%) 0 (0%) 0 (0%)
    30–39 660 (19.7%) 0 (0%) 0 (0%)
    40–49 872 (26.0%) 782 (24.3%) 0 (0%)
    50–59 788 (23.5%) 873 (27.1%) 0 (%)
    60–69 493 (14.7%) 799 (24.9%) 447 (30.0%)
    70–79 289 (8.6%) 761 (23.7%) 782 (52.6%)
    ≥80 26 (0.78%) 259 (17.4%)
Systolic BP (mm Hg) 124.0 (15.4) 146.1 (20.9) 138.9 (18.8)
Diastolic BP (mm Hg) 77.3 (9.6) 87.3 (12.4) NA
Hypertension treatment 736 (22.0%) 579 (38.9%)
Total cholesterol (mg/dl) 192.7 (36.4) 214.5 (48.5) 192.7 (33.2)
LDL cholesterol (mg/dl) 119.6 (31.5) 133.7 (44.1) 113.7 (29.9)
HDL cholesterol (mg/dl) 46.2 (12.7) 54.4 (14.4) 49.2 (14.6)
Triglycerides (mg/dl) 139.3 (106.1) 139.2 (103.7) 148.8 (91.9)
Cholesterol treatment 562 (16.8%) NA
Glucose (mg/dl) 102.9 (23.2) 101.7 (25.1) 105.9 (26.9)
Diabetes treatment 166 (5.0%) 143 (9.6%)
Body mass index (kg/m2) 28.3 (4.7) 27.7 (4.1) 27.4 (3.7)
Cancer 169 (5.0%) 170 (5.3) 424 (28.5%)
Prevalent CVD 303 (9.0%) 1137 (35.4) 434 (29.2%)
Diabetes 274 (8.2%) 236 (7.5) 149 (10.0%)
Obesity 964 (28.8%) 773 (24.5) 304 (20.4%)
Hypertension 1130 (33.7%) 895 (28.3%) NA
Hypercholesterolemia 850 (25.4%) 786 (24.60%) 109 (7.3%)
Smoker 535 (16.0%) 681 (21.4) 57 (3.8%)

BP, Blood pressure; HDL, high-density lipoprotein; LDL, low-density lipoprotein; NA, not applicable.

Distribution of testosterone levels in the reference sample

Table 3 describes the distribution of total and free testosterone levels in the reference sample. The mean and median total testosterone concentrations were 723.8 and 698.7 ng/dl, respectively. For free testosterone, the corresponding mean and median values were 141.8 and 134.0 pg/ml, respectively. Consistent with the approach used for defining reference limits for many other analytes (41, 42), total and free testosterone values below the 2.5th percentile (less than approximately 2 sd below the mean) were deemed low. The 2.5th percentile value for total testosterone was 348.3 ng/dl (12.1 nmol/liter), and for free testosterone 70.0 pg/ml (243 pmol/liter) in the reference sample.

Table 3.

Distribution of total and free testosterone in the FHS reference sample (n = 456)

Total testosterone (ng/dl) Free testosterone (pg/ml)
Mean 723.8 141.8
sd 221.1 45.0
Median 698.7 134.0
Quartile range (Q3–Q1) 296.5 60.0
    99th 1322.0 266.0
    97.5th 1196.6 230.0
    95th 1124.0 222.0
    5th 405.9 77.0
    2.5th 348.3 70.0
    1st 282.0 55.0

To convert total testosterone from nanograms per deciliter to nanomoles per liter, multiply concentrations in nanograms per deciliter by 0.0347. To convert free testosterone from picograms per milliliter to picomoles per liter, multiply concentrations in picograms per milliliter by 3.47.

Distribution and categorization of testosterone levels in FHS broad sample and the EMAS and MrOS samples

The distribution of total and free testosterone levels by decades of age was similar in the three cohorts and revealed the expected age-related decline (Fig. 2 and Supplemental Tables 4 and 5). Because of the higher average age of the MrOS participants than that of the other two cohorts, the prevalence of low total and free testosterone was higher in MrOS than in the other two cohorts; 10.4% of men in the FHS broad sample, 23.5% of men in the EMAS, and 40.3% of men in the MrOS had low total testosterone. The prevalence of low free testosterone was 18.1, 24.0, and 61.4%, respectively, in the FHS, EMAS, and MrOS cohorts. In the FHS broad sample, serum total and free testosterone were associated inversely with age, body mass index, and comorbidity and positively with smoking (Supplemental Table 3); similar associations have been reported previously in the EMAS and MrOS.

An external file that holds a picture, illustration, etc.
Object name is zeg0081182520002.jpg

Fig. 2.

Distribution of total and free testosterone levels by decades of age in the FHS broad sample as well as the EMAS and MrOS validation samples. Means and sd bars are shown. To convert total testosterone from nanograms per deciliter to nanomoles per liter, multiply concentrations in nanograms per deciliter by 0.0347. To convert free testosterone from picograms per milliliter to picomoles per liter, multiply concentrations in picograms per milliliter by 3.47.

Relationship of low testosterone levels with outcomes in the three cohorts

Sexual symptoms, available in the EMAS, were analyzed using multivariable logistic regression models adjusted for age, smoking, and site. Compared with men with normal testosterone levels, men with low total testosterone were more likely to report decreased morning erections (Fig. 3), and the men with low free testosterone were more likely to report decreased morning erections, erectile dysfunction, and decreased frequency of sexual thoughts.

An external file that holds a picture, illustration, etc.
Object name is zeg0081182520003.jpg

Fig. 3.

Association of low total or free testosterone with sexual symptoms, physical dysfunction, DM, or any one of these conditions in the FHS, EMAS, and MrOS cohorts. The odds ratios along with the 95% confidence intervals for the association of total and free testosterone with various outcomes in the three validation cohorts are shown. The composite outcome indicates the following: in FHS, one or more of slow walking speed (walking speed in the lowest 20th percentile), self-reported mobility limitation, or diabetes; in EMAS, one or more of low frequency of morning erections, erectile dysfunction, low frequency of sexual thoughts, difficulty in climbing several stairs, limited in walking more than 1 km, slow walking speed (walking speed in the lowest 20th percentile), or diabetes; in MrOS, one or more of frailty, slow walking speed (walking speed in the lowest 20th percentile), or diabetes.

In general, men with low total or free testosterone were more likely to have low walking speed, frailty, or physical symptoms than those with normal levels (Fig. 3). Thus, EMAS participants with low total or free testosterone were more likely to report difficulty climbing stairs or have low walking speed (in the lowest 20th percentile). In MrOS, men with low total or free testosterone were more likely to have slow walking speed than those with normal testosterone; men with low free testosterone were also more likely to have frailty. As reported previously (20), the FHS participants with low free testosterone were at higher risk of self-reported mobility limitation.

In all three cohorts, the men with low total and free testosterone levels were nearly twice as likely to have DM as those with normal levels (Fig. 3). Similarly, in all three cohorts, men with low total and free testosterone were more likely to have at least one of the following: sexual symptoms (EMAS only), a marker of physical dysfunction, or diabetes (Fig. 3). Sensitivity analyses (not shown) considering the 1st and 5th percentiles, as opposed to the 2.5th, as the threshold value for low testosterone, yielded qualitatively concordant results.


We generated reference limits for total and free testosterone levels in a community-based sample of healthy young men using LC-MS/MS, an accurate method with high precision and accuracy. We demonstrated that values below the proposed lower reference limits were associated with increased risk of conditions that have been associated previously with androgen deficiency (19–27) in three geographically distinct populations. Thus, men deemed to have low total or free testosterone levels had increased prevalence of sexual symptoms (15), physical dysfunction (18–21), and DM (22–27) in one or more cohorts.

Epidemiological studies such as these do not permit inferences about the causal role of testosterone in the three categories of conditions studied in this investigation; reverse causality is possible and cannot be excluded. These conditions should not necessarily be viewed as representative symptoms or conditions resulting from an androgen-deficient state.

The Endocrine Society defined androgen deficiency in men as a syndrome characterized by symptoms and signs and low testosterone levels (1). The occurrence of low testosterone level alone does not constitute androgen deficiency. The prevalence of low total or free testosterone in the three cohorts should not be viewed as indicative of a high prevalence of androgen deficiency in these cohorts or in the general population. Previous analyses of the EMAS (15) and Massachusetts Male Aging Study data (44) have shown that the prevalence of symptomatic androgen deficiency is substantially lower (2–5%) than the prevalence of low testosterone levels. In comparison with FHS and EMAS cohorts, MrOS participants were older and had a higher prevalence of comorbid conditions such as cancer and diabetes and also of low total and free testosterone levels.

This study has several strengths. The FHS reference cohort has many characteristics of an optimum sample described by the International Federation of Clinical Chemistry (40–42). This was a community-based sample of healthy men in sufficiently large numbers (40–42). Unlike some other epidemiological studies, which included only middle-aged and older individuals (10), the FHS included both young and older individuals. The FHS samples were drawn in the morning after overnight fast, as recommended by the Endocrine Society guidelines (1), and stored at −80 C and never thawed. The data have internal consistency, as indicated by the expected inverse association of testosterone with age, body mass index, and comorbid conditions and a positive association with smoking. We used LC-MS/MS, the method with high specificity and accuracy. The consistency of the associations of low testosterone with the prevalence of sexual, physical and metabolic conditions across three geographically distinct samples is noteworthy.

This study also has some limitations. These reference ranges were derived from single morning samples, which discount the pulsatile, diurnal, and circannual rhythms. Symptomatic androgen deficiency designation may not be persistent over time (45). Our analyses show that early morning testosterone levels, obtained in a manner similar to that used by physicians in practice, are associated cross-sectionally with symptoms and clinical outcomes. The mass spectrometry methods used for measuring testosterone concentrations differed across the three cohorts, and the assays from EMAS and MrOS have not been cross-calibrated. The assays were performed in samples stored at −80 C; the stability of SHBG in stored samples cannot be assumed. We determined reference ranges in men 40 yr of age or younger. This age cutoff is admittedly arbitrary because there is no evidence of an inflection point in the trend line at this age. Our approach of generating the reference range in healthy young men is similar to the use of T-scores for bone mineral density. Although for some analytes, it may be appropriate to generate age-adjusted reference ranges (40–42), for others that exhibit substantial age-related change, it may be more appropriate to derive the reference ranges in a healthy, young population. However, it is difficult to determine with certainty at this time whether age-adjusted reference ranges may be needed. Given the white ethnicity of the reference sample, investigations of multiethnic cohorts to evaluate the generalizability of the proposed reference limits is important. Some studies have reported significant geographic and racial differences in sex-steroid levels (46), whereas others have not (47, 48). We calculated free testosterone concentrations using a previously published equation (38); calculated free testosterone concentrations may differ from those measured by the equilibrium dialysis method (49–51). Furthermore, different equations may yield different results depending upon the dissociation constants and the assumptions embedded in the equation. Finally, we cannot exclude the possibility that some men with putative androgen deficiency may have been included in the reference sample.

The lower limit of total testosterone levels in the FHS reference sample is slightly higher than the threshold reported historically (∼300 ng/dl, 10.4 nmol/liter) but closer to the thresholds associated with sexual and physical symptoms in a recent investigation of older men (15). The thresholds for various sexual and metabolic outcomes in men supplemented with graded doses of testosterone after pharmacological suppression of endogenous testosterone production or in men with androgen deficiency receiving replacement doses of testosterone generally have been in the 250- to 400-ng/dl range (39, 52, 53). In contrast to our study, which generated the reference range in healthy men, 19–40 yr of age, using LC-MS/MS, previous epidemiological studies included middle-aged and older men and used immunoassays. We excluded men with comorbid conditions from the reference sample.

Despite these attempts to remove influences of comorbid conditions and other factors, however, there remain many sources of variation that cannot be controlled. Differences in study populations, subject selection, time of sample collection, and testosterone assays may contribute to the differences in normative ranges observed here and in other studies. These reference ranges, generated in a reference sample of healthy, lean young men of the FHS, cannot be applied to other assays in other laboratories without appropriate cross-calibration of assays. Historical experience with cholesterol and hemoglobin A1C assays indicates that the application of reference ranges across laboratories is a challenging process that requires mechanisms for standardizing assays (43, 54). The CDC testosterone standardization effort addresses this challenge and will facilitate the application of these reference ranges across laboratories.

It is likely that the results exhibited here may apply to other thresholds proposed for the lower limit to normative ranges. The proposed reference ranges represent the essential first step in defining androgen deficiency syndrome in men. The data here define only a potential reference interval from a general population; how well these discriminating thresholds can be applied to clinical diagnosis of androgen deficiency syndrome needs further validation using receiver operating characteristic curves in clinical populations. The association of low testosterone defined using these criteria with incident outcomes should be evaluated longitudinally to exclude reverse causality. Ultimately, placebo-controlled, randomized trials would be necessary to determine whether testosterone therapy improves outcomes in men deemed androgen deficient by the presence of testosterone levels below the thresholds reported here and symptoms and signs.


This work was supported by primarily by National Institutes of Health (NIH) Grant 1RO1AG31206 to S.B. and R.S.V. Additional support was provided by the Boston Claude D. Pepper Older Americans Independence Center Grant 5P30AG031679 from the National Institute on Aging (NIA) and by a grant from the CDC Foundation. The Framingham Heart Study is supported by the National Heart, Lung, and Blood Institute’s Framingham Heart Study contract N01-HC-25195. The EMAS is funded by the Commission of the European Communities Fifth Framework Program “Quality of Life and Management of Living Resources” Grant QLK6-CT-2001-00258. The Osteoporotic Fractures in Men (MrOS) Study is supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases, the NIA, the National Center for Research Resources, and NIH Roadmap for Medical Research under the following grant numbers: U01 AR45580;, U01 AR45614;, U01 AR45632;, U01 AR45647;, U01 AR45654;, U01 AR45583;, U01 AG18197;, U01-AG027810;, and UL1 RR024140.

The External Advisory Board included Peter J. Snyder, M.D.; Andre Araujo, Ph.D.; and William Rosner, M.D.

Members of the EMAS Group include A. J. Silman and T. W. O’Neill (Andrology Research Unit, Manchester, UK), G. Bartfai (Albert Szent-Göorgy Medical University, Szeged, Hungary), F. Casanueva (Instituto Salud Carlos III, Santiago de Compostela, Spain), G. Forti (University of Florence, Florence, Italy), A. Giwercman (Malmö University Hospital, University of Lund, Sweden), T. S. Han and M. E. J. Lean (University of Glasgow, Glasgow, Scotland, UK), I. T. Huhtaniemi (Imperial College London, London, UK), K. Kula (Medical University of Lodz, Lodz, Poland), N. Pendleton (The University of Manchester, Hope Hospital, Salford, UK), M. Punab (United Laboratories of Tartu University Clinics, Tartu, Estonia), S. Boonen (Catholic University of Leuven, Leuven, Belgium), and D. Vanderschueren (Centers for Disease Control and Prevention, Atlanta, GA).

Disclosure Summary: The authors have no conflicts in relations to this research.



Cardiovascular disease
diabetes mellitus
European Male Aging Study
Framingham Heart Study
Gen 3
third generation
liquid chromatography tandem mass spectrometry
Osteoporotic Fractures in Men Study.


1. Bhasin S, Cunningham GR, Hayes FJ, Matsumoto AM, Snyder PJ, Swerdloff RS, Montori VM. 2006. Testosterone therapy in adult men with androgen deficiency syndromes: an Endocrine Society clinical practice guideline. J Clin Endocrinol Metab 91:1995–2010 [PubMed] []
2. Bhasin S, Zhang A, Coviello A, Jasuja R, Ulloor J, Singh R, Vesper H, Vasan RS. 2008. The impact of assay quality and reference ranges on clinical decision making in the diagnosis of androgen disorders. Steroids 73:1311–1317 [PubMed] []
3. Rosner W, Auchus RJ, Azziz R, Sluss PM, Raff H. 2007. An Endocrine Society Position Statement: utility, limitations and pitfalls in measuring testosterone. J Clin Endocrinol Metab 92:405–413 [PubMed] []
4. Eskelinen S, Vahlberg T, Isoaho R, Kivelä SL, Irjala K. 2007. Biochemical reference intervals for sex hormones with a new AutoDelfia method in aged men. Clin Chem Lab Med 45:249–253 [PubMed] []
5. Sikaris K, McLachlan RI, Kazlauskas R, de Kretser D, Holden CA, Handelsman DJ. 2005. Reproductive hormone reference intervals for healthy fertile young men: evaluation of automated platform assays. J Clin Endocrinol Metab 90:5928–5936 [PubMed] []
6. Tennekoon KH, Karunanayake EH. 1993. Serum FSH, LH, and testosterone concentrations in presumably fertile men: effect of age. Int J Fertil 38:108–112 [PubMed] []
7. Boyce MJ, Baisley KJ, Clark EV, Warrington SJ. 2004. Are published normal ranges of serum testosterone too high? Results of a cross-sectional survey of serum testosterone and luteinizing hormone in healthy men. BJU Int 94:881–885 [PubMed] []
8. Salameh WA, Redor-Goldman MM, Clarke NJ, Reitz RE, Caulfield MP. 2010. Validation of a total testosterone assay using high-turbulence liquid chromatography tandem mass spectrometry: total and free testosterone reference ranges. Steroids 75:169–175 [PubMed] []
9. Kushnir MM, Rockwood AL, Roberts WL, Pattison EG, Bunker AM, Fitzgerald RL, Meikle AW. 2006. Performance characteristics of a novel tandem mass spectrometry assay for serum testosterone. Clin Chem 52:120–128 [PubMed] []
10. Mohr BA, Guay AT, O’Donnell AB, McKinlay JB. 2005. Normal, bound and nonbound testosterone levels in normally ageing men: results from the Massachusetts Male Ageing Study. Clin Endocrinol (Oxf) 62:64–73 [PubMed] []
11. Wang C, Catlin DH, Demers LM, Starcevic B, Swerdloff RS. 2004. Measurement of total serum testosterone in adult men: comparison of current laboratory methods versus liquid chromatography-tandem mass spectrometry. J Clin Endocrinol Metab 89:534–543 [PubMed] []
12. Taieb J, Mathian B, Millot F, Patricot MC, Mathieu E, Queyrel N, Lacroix I, Somma-Delpero C, Boudou P. 2003. Testosterone measured by 10 immunoassays and by isotope-dilution gas chromatography-mass spectrometry in sera from 116 men, women, and children. Clin Chem 49:1381–1395 [PubMed] []
13. Bhasin S, Wu F. 2006. Making a diagnosis of androgen deficiency in adult men: what to do until all the facts are in? Nat Rev Clin Pract Endocrinol Metab 2:529 [PubMed] []
14. Splansky GL, Corey D, Yang Q, Atwood LD, Cupples LA, Benjamin EJ, D’Agostino RB, Sr, Fox CS, Larson MG, Murabito JM, O’Donnell CJ, Vasan RS, Wolf PA, Levy D. 2007. The Third Generation Cohort of the National Heart, Lung, and Blood Institute’s Framingham Heart Study: design, recruitment, and initial examination. Am J Epidemiol 165:1328–1335 [PubMed] []
15. Wu FC, Tajar A, Beynon JM, Pye SR, Silman AJ, Finn JD, O’Neill TW, Bartfai G, Casanueva FF, Forti G, Giwercman A, Han TS, Kula K, Lean ME, Pendleton N, Punab M, Boonen S, Vanderscheuren D, Labrie F, Huhtaniemi IT; EMAS Group 2010. Identification of late-onset hypogonadism in middle-aged and elderly men. N Engl J Med 363:123–135 [PubMed] []
16. Lee DM, O’Neill TW, Pye SR, Silman AJ, Finn JD, Pendleton N, Tajar A, Bartfai G, Casanueva F, Forti G, Giwercman A, Huhtaniemi IT, Kula K, Punab M, Boonen S, Vanderscheuren D, Wu FC; EMAS Study Group 2009. The European Male Ageing Study (EMAS): design, methods and recruitment. Int J Androl 32:11–24 [PubMed] []
17. Orwoll E, Blank JB, Barrett-Connor E, Cauley J, Cummings S, Ensrud K, Lewis C, Cawthon PM, Marcus R, Marshall LM, McGowan J, Phipps K, Sherman S, Stefanick ML, Stone K. 2005. Design and baseline characteristics of the osteoporotic fractures in men (MrOS) study: a large observational study of the determinants of fracture in older men. Contemp Clin Trials 26:569–585 [PubMed] []
18. Schaap LA, Pluijm SM, Smit JH, van Schoor NM, Visser M, Gooren LJ, Lips P. 2005. The association of sex hormone levels with poor mobility, low muscle strength and incidence of falls among older men and women. Clin Endocrinol (Oxf) 63:152–160 [PubMed] []
19. Krasnoff JB, Basaria S, Pencina MJ, Jasuja GK, Vasan RS, Ulloor J, Zhang A, Coviello A, Kelly-Hayes M, D’Agostino RB, Wolf PA, Bhasin S, Murabito JM. 2010. Free testosterone levels are associated with mobility limitation and physical performance in community-dwelling men: the Framingham Offspring Study. J Clin Endocrinol Metab 95:2790–2799 [PMC free article] [PubMed] []
20. Orwoll E, Lambert LC, Marshall LM, Blank J, Barrett-Connor E, Cauley J, Ensrud K, Cummings SR; Osteoporotic Fractures in Men Study Group 2006. Endogenous testosterone levels, physical performance, and fall risk in older men. Arch Intern Med 166:2124–2131 [PubMed] []
21. Araujo AB, Travison TG, Bhasin S, Esche GR, Williams RE, Clark RV, McKinlay JB. 2008. Association between testosterone and estradiol and age-related decline in physical function in a diverse sample of men. J Am Geriatr Soc 56:2000–2008 [PMC free article] [PubMed] []
22. Haffner SM, Shaten J, Stern MP, Smith GD, Kuller L. 1996. Low levels of sex hormone-binding globulin and testosterone predict the development of non-insulin-dependent diabetes mellitus in men. MRFIT Research Group. Multiple Risk Factor Intervention Trial. Am J Epidemiol 143:889–897 [PubMed] []
23. Stellato RK, Feldman HA, Hamdy O, Horton ES, McKinlay JB. 2000. Testosterone, sex hormone-binding globulin, and the development of type 2 diabetes in middle-aged men: prospective results from the Massachusetts male aging study. Diabetes Care 23:490–494 [PubMed] []
24. Oh JY, Barrett-Connor E, Wedick NM, Wingard DL. 2002. Endogenous sex hormones and the development of type 2 diabetes in older men and women: the Rancho Bernardo Study. Diabetes Care 25:55–60 [PubMed] []
25. Selvin E, Feinleib M, Zhang L, Rohrmann S, Rifai N, Nelson WG, Dobs A, Basaria S, Golden SH, Platz EA. 2007. Androgens and diabetes in men: results from the third National Health and Nutrition Examination Survey (NHANES III). Diabetes Care 30:234–238 [PubMed] []
26. Ding EL, Song Y, Malik VS, Liu S. 2006. Sex differences of endogenous sex hormones and risk of type 2 diabetes: a systematic review and meta-analysis. JAMA 295:1288–1299 [PubMed] []
27. Laaksonen DE, Niskanen L, Punnonen K, Nyyssönen K, Tuomainen TP, Valkonen VP, Salonen R, Salonen JT. 2004. Testosterone and sex hormone-binding globulin predict the metabolic syndrome and diabetes in middle-aged men. Diabetes Care 27:1036–1041 [PubMed] []
28. Rosow I, Breslau N. 1966. A Guttman health scale for the aged. J Gerontol 21:556–559 [PubMed] []
29. Beckett LA, Brock DB, Lemke JH, Mendes de Leon CF, Guralnik JM, Fillenbaum GG, Branch LG, Wetle TT, Evans DA. 1996. Analysis of change in self-reported physical function among older persons in four population studies. Am J Epidemiol 143:766–778 [PubMed] []
30. Crawford SL, Jette AM, Tennstedt SL. 1997. Test-retest reliability of self-reported disability measures in older adults. J Am Geriatr Soc 45:338–341 [PubMed] []
31. Cawthon PM, Fullman RL, Marshall L, Mackey DC, Fink HA, Cauley JA, Cummings SR, Orwoll ES, Ensrud KE; Ostoporotic Fractures in Men (MrOS) Research Group 2008. Physical performance and risk of hip fractures in older men. J Bone Mineral Res 23:1037–1044 [PMC free article] [PubMed] []
32. Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, Seeman T, Tracy R, Kop WJ, Burke G, McBurnie MA; Cardiovascular Health Study Collaborative Research Group 2001. Frailty in older adults: evidence of a phenotype. J Gerontol A Biol Sci Med Sci 56:M146–M156 [PubMed] []
33. Cawthon PM, Ensrud KE, Laughlin GA, Cauley JA, Dam TT, Barrett-Connor E, Fink HA, Hoffman AR, Lau E, Lane NE, Stefanick ML, Cummings SR, Orwoll ES; the Osteoporotic Fractures in Men (MrOS) Study 2009. Sex hormones and frailty in older men: the Osteoporotic Fractures in Men (MrOS) Study. J Clin Endocrinol Metab 94:3806–3815 [PMC free article] [PubMed] []
34. Ingelsson E, Massaro JM, Sutherland P, Jacques PF, Levy D, D’Agostino RB, Vasan RS, Robins SJ. 2009. Contemporary trends in dyslipidemia in the Framingham Heart Study. Arch Intern Med 169:279–286 [PMC free article] [PubMed] []
35. Sir-Petermann T, Codner E, Pérez V, Echiburú B, Maliqueo M, Ladrón de Guevara A, Preisler J, Crisosto N, Sánchez F, Cassorla F, Bhasin S. 2009. Metabolic and reproductive features before and during puberty in daughters of women with polycystic ovary syndrome. J Clin Endocrinol Metab 94:1923–1930 [PMC free article] [PubMed] []
36. Labrie F, Bélanger A, Bélanger P, Bérubé R, Martel C, Cusan L, Gomez J, Candas B, Castiel I, Chaussade V, Deloche C, Leclaire J. 2006. Androgen glucoronides instead of testosterone as the new marker of androgenic activity in women. J Steroid Biochem Mol Biol 99:182–188 [PubMed] []
37. LeBlanc ES, Nielson CM, Marshall LM, Lapidus JA, Barrett-Connor E, Ensrud KE, Hoffman AR, Laughlin G, Ohlsson C, Orwoll ES; Osteoporotic Fractures in Men Study Group 2009. The effects of serum testosterone, estradiol, and sex hormone binding globulin levels on fracture risk in older men. J Clin Endocrinol Metab 94:3337–3346 [PMC free article] [PubMed] []
38. Mazer NA. 2009. A novel spreadsheet method for calculating the free serum concentrations of testosterone, dihydrotestosterone, estradiol, estrone and cortisol: with illustrative examples from male and female populations. Steroids 74:512–519 [PubMed] []
39. Bhasin S, Woodhouse L, Casaburi R, Singh AB, Bhasin D, Berman N, Chen X, Yarasheski KE, Magliano L, Dzekov C, Dzekov J, Bross R, Phillips J, Sinha-Hikim I, Shen R, Storer TW. 2001. Testosterone dose-response relationships in healthy young men. Am J Physiol Endocrinol Metab 281:E1172–E1181 [PubMed] []
40. Lott JA, Mitchell LC, Moeschberger ML, Sutherland DE. 1992. Estimation of reference ranges: how many subjects are needed? Clin Chem 38:648–650 [PubMed] []
41. Solberg HE. 1987. Approved recommendations (1987) on the theory of reference values, II: selection of individuals for the production of reference values. J Clin Chem Clin Biochem 25:639–644 []
42. Elveback LR. 1973. The population of healthy persons as a source of reference information. Hum Pathol 4:9–16 [PubMed] []
43. Myers GL, Cooper GR, Winn CL, Smith SJ. 1989. The Centers for Disease Control-National Heart, Lung and Blood Institute Lipid Standardization Program. An approach to accurate and precise lipid measurements. Clin Lab Med 9:105–135 [PubMed] []
44. Araujo AB, Esche GR, Kupelian V, O’Donnell AB, Travison TG, Williams RE, Clark RV, McKinlay JB. 2007. Prevalence of symptomatic androgen deficiency in men. J Clin Endocrinol Metab 92:4241–4247 [PubMed] []
45. Travison TG, Shackelton R, Araujo AB, Hall SA, Williams RE, Clark RV, O’Donnell AB, McKinlay JB. 2008. The natural history of symptomatic androgen deficiency in men: onset, progression, and spontaneous remission. J Am Geriatr Soc 56:831–839 [PMC free article] [PubMed] []
46. Orwoll ES, Nielson CM, Labrie F, Barrett-Connor E, Cauley JA, Cummings SR, Ensrud K, Karlsson M, Lau E, Leung PC, Lungren O, Mellstrom D, Patrick AL, Stefanick ML, Nakamura K, Yoshimura N, ZMuda J, Vandeput L, Ohlsson C; Osteoporotic Fractures in Men (MrOS) Research Group 2010. Evidence for geographical and racial variation in serum sex steroid levels in older men. J Clin Endocrinol Metab 95:E151–E160 [PMC free article] [PubMed] []
47. Litman HJ, Bhasin S, Link CL, Araujo AB, McKinlay JB. 2006. Serum androgen levels in Black, Hispanic, and White men. J Clin Endocrinol Metab 91:4326–4334 [PubMed] []
48. Wu FC, Tajar A, Pye SR, Silman AJ, Silman AJ, Finn JD, O’Neill TW, Bartfai G, Casanueva F, Forti G, Giwercman A, Huhtaniemi IT, Kula K, Punab M, Boonen S, Vanderscheuren D; European Male Aging Study Group 2008. Hypothalamic-pituitary-testicular axis disruptions in older men are differentially linked to age and modifiable risk factors: the European Male Aging Study. J Clin Endocrinol Metab 93:2737–2734 [PubMed] []
49. Sartorius G, Ly LP, Sikaris K, McLachlan R, Handelsman DJ. 2009. Predictive accuracy and sources of variability in calculated free testosterone estimates. Ann Clin Biochem 46:137–143 [PubMed] []
50. Ly LP, Sartorius G, Hull L, Leung A, Swerdloff RS, Wang C, Handelsman DJ. 2010. Accuracy of calculated free testosterone formulae in men. Clin Endocrinol. (Oxf) 73:382–388 [PubMed] []
51. Wartofsky L, Handelsman DJ. 2010. Standardization of hormonal assays for the 21st century. J Clin Endocrinol Metab 95:5141–5143 [PubMed] []
52. Zitzmann M, Faber S, Nieschlag E. 2006. Association of specific symptoms and metabolic risks with serum testosterone in older men. J Clin Endocrinol Metab 91:4335–4343 [PubMed] []
53. Kelleher S, Conway AJ, Handelsman DJ. 2004. Blood testosterone threshold for androgen deficiency symptoms. J Clin Endocrinol Metab 89:3813–3817 [PubMed] []
54. Little RR, Rohlfing CL, Wiedmeyer HM, Myers GL, Sacks DB, Goldstein DE. 2001. The National Glycohemoglobin Standardization Program: a 5-year progress report. Clin Chem 47:1985–1992 [PubMed] []

Six Penile Cancer Symptoms You Need to Pay Attention To

penis cancer incidence

penis cancer incidenceCancer of the penis (penile cancer) is probably one of the least talked about cancer types, but can be just as deadly as other cancers. For this reason, like with all cancers, the sooner you get to a doctor and start treatment, the better. Let’s look at six symptoms you should pay attention to, because they may be warning signs of penile cancer.

  1. A Sore or Growth on the Penis – If you see a sore or wart-like growth on your penis, and it doesn’t heal after a week, it’s time to see a doctor. Although this may be something non-life threatening, it could be a symptom of an STD or penis cancer.
    Hover to reveal the location on the map.
  2. Other Changes of the Penile Skin – The skin of the penis is often the first sign of penis cancer, so if you see any changes to your penis’s skin, see your doctor. These include: red, velvety rash, crusty bumps or flat, bluish to brown lumps.
  3. Bleeding from the Penis – If you experience bleeding from the penis, this could be a sign of cancer. Or it may be something less severe, such as a urinary tract infection or STD. Either way, it’s definitely a symptom that should be looked at by your doctor immediately.
  4. Bleeding from under the Foreskin – This may also be a sign of penile cancer. In addition to bleeding, if there’s a foul-smelling discharge coming from your foreskin, or you find it hard to draw your foreskin back from your glans – see a doctor.
    .Hover to reveal the location on the map.
  5. Penile Swelling – Swelling at the end of your penis is another symptom that should be looked at by your physician immediately.
  6. Groin Area Lumps – If penis cancer spreads, it often first spreads to the lymph glands located in the groin area. This can then often be felt as lumps under the skin. However, swelling of lymph nodes may also mean your body is responding to an infection. Either way, a trip to the doctor is definitely needed.
    Penile Cancer lymph nodes.

Although penile cancer is not common, any changes in your penis’s health should be cause for your concern. If anything strange appears, see your doctor. It’s better that you go to the doctor and it be nothing, then not go and miss out on early treatment.