Abstract
Summary
Background and objectives
Fibroblast growth factor 23 (FGF23) regulates phosphorus and vitamin D metabolism. Elevated FGF23 concentrations are associated with cardiovascular disease events and mortality across a broad range of kidney function, but the predictors of FGF23 concentrations in the general population are unclear.
Design, setting, participants, & measurements
We examined cross-sectional associations of dietary and nondietary parameters with plasma FGF23 in 1261 participants of the Health Professionals Follow-up Study (mean age 64 ± 9, mean creatinine 0.9 ± 0.2 mg/dl, mean FGF23 64 ± 28 RU/ml).
Results
In multivariable-adjusted analyses, each 5-year increase in age was associated with 2.1 RU/ml higher FGF23, each 500-mg increase in phosphorus intake was associated with 3.4 RU/ml higher FGF23, and each 0.1-mg/dl increase in creatinine was associated with 3.4 RU/ml higher FGF23. Participants in the highest category of body mass index had 9.5 RU/ml higher FGF23 than those in the lowest, smokers had 17.1 RU/ml higher FGF23 than nonsmokers, and participants with hypertension had 6.0 RU/ml higher FGF23 than those without hypertension. With respect to biochemical parameters, higher parathyroid hormone, phosphate, uric acid, and triglyceride levels all were associated independently with higher FGF23 in models adjusted for age, creatinine, and other factors. In a subset of 748 participants with available data, some inflammatory biomarkers were associated independently with higher FGF23.
Conclusions
In community-dwelling adults with largely preserved kidney function, established cardiovascular risk factors and higher phosphorus intake were associated with higher FGF23. These results might explain the link between FGF23 and cardiovascular disease.
Introduction
Fibroblast growth factor 23 (FGF23) is a bone-derived hormone that regulates phosphorus and vitamin D metabolism (1). Increased FGF23 levels have emerged as a novel risk factor for cardiovascular disease events, kidney disease progression, and death among individuals with chronic kidney disease (CKD) (2–6). Increased FGF23 levels have also been associated with higher risks of heart failure, stroke, and death among individuals with mostly preserved kidney function (7). Together, these data have generated considerable interest in elucidating reasons for the link between FGF23 and adverse health outcomes.
Previous studies examining the associations of FGF23 with known risk factors for cardiovascular disease primarily focused on CKD patients (8–10). Less is known about these associations in individuals with normal kidney function. Population-based studies of individuals with preserved kidney function reported that elevated FGF23 levels were associated with obesity, inflammation, smoking, and dyslipidemia (7,11,12), all of which are strongly associated with cardiovascular morbidity and mortality and, as such, may help explain a link between FGF23 and adverse outcomes. However, the associations of FGF23 with established cardiovascular risk factors in these studies were either unadjusted or inconsistently adjusted for key potential confounders such as parathyroid hormone (PTH) levels, making it difficult to ascertain which factors were independently correlated with higher FGF23 levels or could serve as potential confounders of these relationships. Moreover, none of these studies examined associations of dietary factors with FGF23, which is critical for interpreting a link between obesity and dyslipidemia with increased FGF23.
To identify factors independently associated with higher plasma FGF23 concentrations in community-dwelling adults with preserved kidney function, including traditional and nontraditional risk factors for cardiovascular disease, we examined cross-sectional associations of demographic, clinical, dietary, and laboratory factors with FGF23 levels in 1261 participants of the Health Professionals Follow-up Study.
Materials and Methods
Source Population
The Health Professionals Follow-up Study enrolled 51,529 male dentists, optometrists, osteopaths, pharmacists, podiatrists, and veterinarians who were 40 to 75 years of age in 1986. At baseline, study participants filled out a detailed questionnaire about diet, medical history, and medications. Subsequent questionnaires have been mailed every 2 years to update information on health-related behaviors, medications, and medical events. Between 1993 and 1995, blood samples were submitted by 18,225 participants. The participants for this study were selected from a nested prospective case-control study of incident coronary heart disease and were free of cardiovascular disease at blood draw (13). Two controls were selected for each case and matched on age, month, and year of blood collection, and smoking status. The institutional review board at Brigham and Women's Hospital reviewed and approved the study.
Measurements
Biochemical Variables.
Plasma FGF23 levels were measured using a second-generation C-terminal human enzyme-linked immunosorbent assay (Immutopics, San Clemente, CA). The coefficient of variation (CV) was 9.8%. Plasma levels were measured in duplicate in each participant, and the results were averaged. Phosphate was measured using the Hitachi 917 analyzer (Roche Applied Science) with CV of 8.0%. Intact PTH was measured by electrochemiluminescence immunoassay on the 2010 Elecsys autoanalyzer (Roche Applied Science) with CV of 8.3%. Assays and CVs for plasma 25-hydroxyvitamin D (25(OH)D), creatinine, lipoproteins, lipids, and inflammatory biomarkers in this population were previously described (14–17).
Diet History.
The self-administered semiquantitative food frequency questionnaire (FFQ) completed closest to the blood draw was used to assess average nutrient intake over the past year. The median time between the FFQ and blood measurements was 2 months. In addition to questions on over 130 individual food items and 22 individual beverages, the FFQ inquired about the use of calcium supplements, vitamin D supplements, and multivitamins. Intake of specific dietary factors was computed from the reported frequency of consumption of each specified unit of food and from United States Department of Agriculture data. The values for various nutrients from the FFQ have been extensively validated (18–20).
Anthropometric Data, Medical History, and Lifestyle Factors.
Information on age, weight, and height was obtained on the baseline questionnaire. Age and weight were updated every 2 years. Body mass index (BMI) was calculated as the weight in kilograms divided by the square of height in meters, with weight being obtained from the questionnaire closest to the time of blood draw. Smoking status (never, past, or current), physical activity, and alcohol intake were ascertained from the biennial questionnaire closest to the time of blood draw (21,22). Information on hypertension, diabetes mellitus, gout, and kidney stones was obtained from biennial questionnaires.
Statistical Analyses
We excluded nine participants with grossly hemolyzed blood samples. The distributions of FGF23 and phosphate were right skewed. To minimize the effect of extreme outliers, we excluded participants with FGF23 and phosphate plasma levels in the top 1% of each distribution (12 participants). After these exclusions, the study population consisted of 1261 men.
Demographic, clinical, and laboratory characteristics were compared across quartiles of FGF23 using univariable linear regression to generate P values for trend for continuous variables and the chi-squared test for categorical variables. Analysis of covariance was used to generate the mean intakes of each dietary factor by quartile of FGF23. For each quartile, the mean intakes were adjusted for the following variables: age (continuous), BMI (continuous), plasma creatinine (continuous), self-reported histories of hypertension, diabetes, and gout (all yes or no), smoking status (current, past, or never), and development of coronary heart disease after blood draw (yes or no). Intakes of each dietary factor (except for total protein, carbohydrate, and fat expressed as fraction of caloric intake) were also adjusted for total caloric intake. Because the FFQ may incompletely capture intake of inorganic forms of dietary phosphorus (i.e., phosphorus-based food preservatives) (23), we also examined the frequency of intake of foods commonly enriched with additives (processed meats, colas) across quartiles of FGF23, adjusted for the same covariates.
We utilized multivariable linear regression models to examine independent correlates of FGF23. Candidate independent variables included the following potential confounders plus factors that were significantly associated with FGF23 in unadjusted analyses: age (four categories, ≤55, 56 to 65, 66 to 75, >75 years); race (Caucasian or other); BMI (four categories, <23, 23 to 24, 25 to 29, ≥30 kg/m2); physical activity; fasting status at time of blood draw; geographic region of residence (Northeast, South, or Midwest); season of blood draw (winter, spring, summer, or fall); use of thiazide diuretics (yes or no); use of aspirin (≥2 times/wk or <2 times/wk); use of a statin (yes or no); smoking status; history of hypertension, diabetes, gout, kidney stones, or high cholesterol; and intakes of alcohol, total calcium (dietary plus supplemental), phosphorus, animal protein, vegetable protein, total fat, fructose, potassium, magnesium, phytate, and 25(OH)D (all in quartiles). We included age, plasma creatinine, and development of coronary heart disease after blood draw in all multivariable models. Other variables were excluded from the final multivariable model if they were not associated with the outcome or were not confounders (change in regression coefficient <10%). For models examining plasma factors, we considered plasma levels of the following (all in quartiles): phosphate, PTH, uric acid, 25(OH)D, total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides, and C-reactive protein (CRP). In a subset of 748 participants with available data, we also examined plasma levels of hemoglobin A1c, adiponectin, interleukin 6 (IL-6), vascular cell adhesion molecule 1, intercellular adhesion molecule 1, and soluble TNF receptors 1 and 2 (markers of TNF-α activity). For tests of trend, we modeled the median value of quartiles as continuous variables in the regression model.
FGF23 was not associated with incident coronary heart disease in our study population (13). However, by design, 422 participants developed coronary heart disease after blood draw. Therefore, we performed separate analyses of participants who did and who did not develop coronary heart disease. In addition, we conducted sensitivity analyses weighted by the inverse conditional probability of being included in the case-control sample. Finally, because decreased kidney function is strongly associated with higher FGF23 levels, we performed further sensitivity analyses excluding individuals with eGFR <60 ml/min per 1.73 m2. We calculated 95% confidence intervals for all point estimates. All P values were two tailed. The data were analyzed by using SAS software, version 9.1 (SAS Institute Inc., Cary, NC).
Results
Population Characteristics
The mean age of the study population was 64 ± 9 years, the mean creatinine was 0.9 ± 0.2 mg/dl, and the mean plasma FGF23 concentration was 64 ± 28 relative units (RU)/ml. Over 94% of the study sample self-reported Caucasian race, with the rest being Asian, African American, or “other.” Table 1 depicts demographic, clinical, and laboratory characteristics of study participants according to quartiles of FGF23. Participants in higher quartiles of FGF23 were older, had higher BMI, and lower eGFR and were more likely to be current smokers and have a history of hypertension or gout. In addition, participants in higher quartiles of FGF23 had higher mean concentrations of phosphate, PTH, uric acid, and triglycerides, and lower mean concentrations of HDL.
Table 1.
Participant demographic, clinical, and laboratory characteristics according to quartile of fibroblast growth factor 23
| FGF23 Q1 (<48 RU/ml) | FGF23 Q2 (48 to 58 RU/ml) | FGF23 Q3 (59 to 73 RU/ml) | FGF23 Q4 (>73 RU/ml) | P for Trend | |
|---|---|---|---|---|---|
| n | 315 | 315 | 316 | 315 | |
| Age | 63 ± 8 | 63 ± 9 | 64 ± 9 | 66 ± 8 | <0.01 |
| Body mass index (kg/m2) | 25 ± 3 | 25 ± 3 | 26 ± 3 | 26 ± 4 | 0.01 |
| eGFR (ml/min per 1.73 m2) | 91 ± 20 | 88 ± 20 | 84 ± 16 | 81 ± 20 | <0.01 |
| Smoking (%) | 0.07 | ||||
| never | 44 | 41 | 41 | 36 | |
| past | 46 | 46 | 47 | 45 | |
| current | 4 | 9 | 7 | 15 | |
| other/unknown | 6 | 4 | 5 | 4 | |
| Comorbidities (%) | |||||
| hypertension | 27 | 24 | 34 | 44 | <0.01 |
| diabetes | 5 | 6 | 4 | 7 | 0.31 |
| hyperlipidemia | 39 | 45 | 46 | 48 | 0.14 |
| nephrolithiasis | 11 | 12 | 11 | 9 | 0.78 |
| gout | 7 | 7 | 11 | 13 | 0.06 |
| Laboratory | |||||
| FGF23 (RU/ml) | 40 ± 6 | 52 ± 3 | 64 ± 4 | 101 ± 33 | <0.01 |
| creatinine (mg/dl) | 0.9 ± 0.2 | 1.0 ± 0.2 | 1.0 ± 0.2 | 1.0 ± 0.3 | <0.01 |
| phosphate (mg/dl) | 2.8 ± 0.6 | 2.8 ± 0.6 | 2.9 ± 0.5 | 2.9 ± 0.5 | <0.01 |
| PTH (pg/ml) | 37 ± 12 | 37 ± 12 | 38 ± 14 | 42 ± 17 | <0.01 |
| uric acid (mg/dl) | 5.5 ± 1.2 | 5.7 ± 1.2 | 5.9 ± 1.1 | 6.3 ± 1.4 | <0.01 |
| 25(OH)D (ng/dl) | 23 ± 7 | 24 ± 8 | 25 ± 9 | 24 ± 8 | 0.79 |
| total cholesterol (mg/dl) | 205 ± 35 | 206 ± 36 | 206 ± 37 | 206 ± 39 | 0.71 |
| HDL (mg/dl) | 47 ± 11 | 46 ± 13 | 44 ± 12 | 42 ± 13 | <0.01 |
| LDL (mg/dl) | 130 ± 30 | 131 ± 32 | 128 ± 33 | 128 ± 34 | 0.08 |
| triglycerides (mg/dl) | 134 ± 111 | 135 ± 81 | 160 ± 96 | 175 ± 115 | <0.01 |
The results are presented as the means ± standard deviation or as frequencies. FGF23, fibroblast growth factor 23; eGFR, estimated GFR; PTH, parathyroid hormone; 25(OH)D, 25-hydroxyvitamin D; RU, relative units; Q, quartile.
Diet characteristics of study participants are summarized according to quartile of FGF23 in Table 2. Adjusted mean daily intake of dietary phosphorus significantly increased with increasing quartiles of FGF23 (P for trend 0.03). In contrast, adjusted mean intakes of protein, calcium, and phytate did not differ across quartiles of FGF23. Similarly, there were no differences in the frequency of intake of foods commonly enriched with phosphorus-based food additives (processed meats, colas) across FGF23 quartiles.
Table 2.
Diet characteristics of participants by quartile of fibroblast growth factor 23
| FGF23 Q1 (<48 RU/ml) | FGF23 Q2 (48 to 58 RU/ml) | FGF23 Q3 (59 to 73 RU/ml) | FGF23 Q4 (>73 RU/ml) | P for trend | |
|---|---|---|---|---|---|
| n | 315 | 315 | 316 | 315 | |
| Total calories | |||||
| Percentage of protein (mean) | 17.2 (16.8, 17.5) | 17.3 (16.9, 17.6) | 17.6 (17.3, 17.9) | 17.2 (16.8, 17.5) | 0.95 |
| Percentage of carbohydrates (mean) | 50.2 (49.3, 51.2) | 50.9 (49.9, 51.8) | 50.6 (49.6, 51.5) | 51.1 (50.1, 52.1) | 0.33 |
| Percentage of Fat (mean) | 29.9 (29.1, 30.7) | 30.4 (29.6, 31.3) | 30.2 (29.5, 30.9) | 30.5 (29.7, 31.3) | 0.38 |
| Protein | |||||
| vegetable (g/d) | 27.5 (26.7, 28.2) | 27.4 (26.6, 28.1) | 27.6 (26.8, 28.4) | 27.3 (26.5, 28.1) | 0.84 |
| animal (g/d) | 59.2 (57.4, 61.2) | 59.9 (58.1, 61.8) | 61.6 (59.7, 63.4) | 60.2 (58.3, 62.1) | 0.50 |
| Phosphorus (mg/d) | 1451 (1422, 1479) | 1459 (1430, 1488) | 1489 (1461, 1518) | 1495 (1465, 1524) | 0.03 |
| Calcium (mg/d) | 938 (893, 982) | 929 (886, 974) | 950 (906, 995) | 978 (932, 1023) | 0.15 |
| Phytate (mg/d) | 1066 (1027, 1105) | 1034 (995, 1074) | 1051 (1012, 1090) | 1025 (985, 1065) | 0.23 |
| Colas (servings/d) | 0.6 (0.5, 0.7) | 0.7 (0.6, 0.8) | 0.6 (0.5, 0.7) | 0.7 (0.6, 0.8) | 0.11 |
| Processed meats (servings/d) | 0.8 (0.4, 1.1) | 0.8 (0.5, 1.2) | 0.7 (0.3, 1.0) | 1.0 (0.6, 1.3) | 0.51 |
The results are depicted as mean intakes (95% confidence interval) adjusted for age, body mass index, creatinine, hypertension, diabetes, gout, smoking, and coronary heart disease. Intakes of each dietary factor (except for total protein, carbohydrate, and fat expressed as fraction of caloric intake) were also adjusted for total caloric intake. FGF23, fibroblast growth factor 23; RU, relative units; Q, quartile.
Factors Associated with FGF23 Concentrations
Table 3 depicts multivariable-adjusted differences in FGF23 by specific demographic, dietary, and clinical factors. Increasing age, dietary phosphorus intake, and creatinine were associated with increasing FGF23 concentrations. When examined as continuous predictor variables, each 5-year increase in age was associated with 2.1 RU/ml higher FGF23 (P < 0.001), each 500-mg increase in daily phosphorus intake was associated with 3.4 RU/ml higher FGF23 (P = 0.02), and each 0.1 mg/dl increase in creatinine was associated with 3.4 RU/ml higher FGF23 (P < 0.001). In addition, participants in the highest category of BMI (≥30 kg/m2) had 9.5 RU/ml higher FGF23 concentrations as compared with participants in the lowest category of BMI (<23 kg/m2), and participants with hypertension or who were current smokers had 6.0 and 17.1 RU/ml higher FGF23 concentrations than participants who did not have hypertension or were nonsmokers, respectively (P < 0.001 for both).
Table 3.
Multivariable-adjusted differences in FGF23 levels by demographic, dietary, and clinical factors
| Variable | Difference in FGF23 (RU/ml) | P for Trend |
|---|---|---|
| Age (years) | <0.01 | |
| category 1 (≤55) | referent | |
| category 2 (56 to 65) | 2.3 (−1.9, 6.5) | |
| category 3 (66 to 75) | 7.1 (2.8, 11.3) | |
| category 4 (>75) | 10.1 (3.8, 16.3) | |
| Body mass index (kg/m2) | 0.06 | |
| category 1 (<23) | referent | |
| category 2 (23 to 24) | 0.2 (−4.5, 4.8) | |
| category 3 (25 to 29) | 0.7 (−3.6, 4.9) | |
| category 4 (≥30) | 9.5 (3.5, 15.5) | |
| Diet phosphorus (mg/day) | 0.09 | |
| quartile 1 (≤1119) | referent | |
| quartile 2 (1120 to 1420) | 0.7 (−3.8, 5.3) | |
| quartile 3 (1421 to 1757) | 2.8 (−2.4, 8.1) | |
| quartile 4 (≥1759) | 8.8 (1.9, 15.6) | |
| Hypertension | 6.0 (2.6, 9.4) | <0.01 |
| Diabetes | −1.6 (−8.3, 5.1) | 0.59 |
| Gout | 3.5 (−1.8, 8.8) | 0.20 |
| Current smoking | 17.1 (11.4, 22.7) | <0.01 |
| Creatinine (per 0.1 mg/dl increase) | 3.4 (2.7, 4.2) | <0.01 |
The results are depicted as regression coefficients (95% confidence interval) adjusted for the listed variables, total caloric intake, and coronary heart disease. FGF23, fibroblast growth factor 23; RU, relative units.
Table 4 depicts multivariable-adjusted differences in FGF23 concentrations by categories of plasma factors in the full study sample and in the subset of participants with available measurements of inflammatory markers. Increasing quartiles of PTH, serum phosphate, uric acid, and triglycerides were significantly associated with increasing FGF23 levels independently of each other and age, BMI, creatinine, hypertension, diabetes, smoking status, and coronary heart disease. In the full multivariable-adjusted model, in addition to PTH, serum phosphate, uric acid, and triglycerides, higher age, creatinine, current smoking, and a history of hypertension remained independent predictors of higher plasma FGF23 concentrations. In the subset of 748 participants with available inflammatory biomarkers, the highest quartiles of IL-6, vascular cell adhesion molecule 1, and soluble tumor necrosis factor receptor 1 were all associated with increased FGF23 as compared with the lowest quartile of each respective analyte in multivariable-adjusted models. In contrast, there were no independent associations between quartiles of CRP, intercellular adhesion molecule 1, or soluble tumor necrosis factor receptor 2 and FGF23. There were no appreciable differences in any of these associations in prespecified analyses stratified by the development of coronary heart disease in study participants. In addition, the results were qualitatively the same in analyses excluding individuals with eGFR <60 ml/min per 1.73 m2 and weighted by the inverse conditional probability of being included in the case-control sample.
Table 4.
Multivariable-adjusted differences in FGF23 levels by categories of plasma factors in the full study sample and in the subset of participants with measurements of inflammatory biomarkers
| Variable | Difference in FGF23 (RU/ml) | P for Trend |
|---|---|---|
| Full study sample (n = 1261)a | ||
| Parathyroid hormone (pg/ml) | 0.03 | |
| quartile 1 (≤29) | referent | |
| quartile 2 (30 to 36) | −0.3 (−4.4, 3.9) | |
| quartile 3 (37 to 45) | −1.3 (−5.4, 2.9) | |
| quartile 4 (>45) | 5.0 (0.8, 9.3) | |
| Phosphate (mg/dl) | <0.01 | |
| quartile 1 (≤2.4) | referent | |
| quartile 2 (2.5 to 2.8) | 5.1 (1.0, 9.2) | |
| quartile 3 (2.9 to 3.1) | 2.7 (−1.8, 7.2) | |
| quartile 4 (>3.1) | 9.9 (5.7, 14.2) | |
| Uric acid (mg/dl) | <0.01 | |
| quartile 1 (≤5.0) | referent | |
| quartile 2 (5.1 to 5.7) | 2.7 (−1.4, 6.9) | |
| quartile 3 (5.8 to 6.5) | 5.8 (1.5, 10.1) | |
| quartile 4 (>6.5) | 8.2 (3.8, 12.7) | |
| Triglycerides (mg/dl) | <0.01 | |
| quartile 1 (≤88) | referent | |
| quartile 2 (89 to 124) | 1.6 (−2.5, 5.8) | |
| quartile 3 (125 to 182) | 2.2 (−2.1, 6.4) | |
| quartile 4 (>182) | 7.2 (2.9, 11.7) | |
| Inflammatory biomarkers (n = 748)b | ||
| IL-6 (pg/ml) | <0.01 | |
| quartile 1 (<1.01) | referent | |
| quartile 2 (1.0 to 1.65) | −0.9 (−6.2, 4.5) | |
| quartile 3 (1.66 to 2.89) | −2.9 (−8.4, 2.7) | |
| quartile 4 (>2.89) | 9.8 (3.9, 15.6) | |
| VCAM1 (ng/ml) | 0.04 | |
| quartile 1 (≤1100) | referent | |
| quartile 2 (1101 to 1291) | 0.68 (−4.6, 5.9) | |
| quartile 3 (1292 to 1495) | 2.4 (−3.1, 7.8) | |
| sTNFR1 (pg/ml) | 0.05 | |
| quartile 1 (<1171) | referent | |
| quartile 2 (1172 to 1383) | 1.9 (−3.4, 7.4) | |
| quartile 3 (1384 to 1691) | 3.1 (−2.7, 8.8) | |
| quartile 4 (>1691) | 9.7 (3.3, 16.0) |
The results are depicted as regression coefficients (95% confidence interval). FGF23, fibroblast growth factor 23; VCAM1, vascular cell adhesion molecule 1; sTNFR1, soluble tumor necrosis factor receptor 1; RU, relative units.
Model adjusted for the listed variables, age, body mass index, creatinine, hypertension, diabetes, smoking status, and coronary heart disease.
Model adjusted for listed variables, age, body mass index, creatinine, hypertension, diabetes, smoking status, plasma levels of PTH, phosphate, uric acid, triglycerides, and coronary heart disease.
Discussion
In this cross-sectional study of community-living men with largely preserved kidney function, higher age, BMI, phosphorus intake, current smoking, and a history of hypertension were independently associated with higher plasma FGF23 concentrations. In addition, higher levels of PTH, phosphate, triglycerides, uric acid, and some biomarkers of inflammation were independently associated with higher FGF23. These findings provide novel insights into the spectrum of demographic, dietary, and biochemical factors that associate with higher plasma FGF23 concentrations in the general population. The associations of increased FGF23 with factors independently linked with excess cardiovascular disease risk—including obesity, dyslipidemia, smoking, and hypertension—may help delineate reasons for the relationship between excess FGF23 and adverse outcomes in individuals across the spectrum of kidney function.
Our results confirm and extend those of prior studies that examined correlates of increased FGF23 in non-CKD populations. In a study of 833 participants of the Heart and Soul Study with mean eGFR of 76 ± 23 ml/min per 1.73 m2, smoking, diabetes, lower eGFR, and higher serum levels of CRP, phosphate, and calcium were all associated with higher plasma FGF23 concentrations (7). However, these associations were either unadjusted or unable to be adjusted for major confounders such as PTH, leaving it unclear as to which factors were independently correlated with higher FGF23 in this study. Marsell et al. (24) examined biochemical predictors of FGF23 in 1000 elderly men with no history of kidney disease (mean eGFR 76 ± 22) and found that eGFR and PTH levels were the only factors significantly associated with FGF23 levels in multivariable-adjusted models. Notably, demographic and clinical variables were not included in the models. In a more recent study of nearly 2000 elderly Swedish individuals with normal kidney function, higher serum FGF23 levels were associated with higher body weight and waist circumference and greater likelihood of having dyslipidemia, independently of age, gender, serum phosphate, serum calcium, 25(OH)D, PTH, and eGFR (11). Importantly, dietary parameters were not available in this or any of the previous data sets. As such, our findings expand upon this prior work by showing that higher BMI, PTH, serum phosphate, creatinine, and triglycerides remain independent predictors of higher FGF23 among individuals with mostly preserved kidney function, even after adjusting for key demographic, clinical, and dietary covariates.
Previous studies showed a robust dose-response relationship between increased FGF23 levels with future cardiovascular disease events and death in both CKD and non-CKD populations (2,3,5,7). In contrast, FGF23 levels were not associated with fatal coronary heart disease or nonfatal myocardial infarction in the participants of this study (13), consistent with a prior study that showed no association of higher FGF23 levels with future myocardial infarction in Heart and Soul Study participants (7). Importantly, higher FGF23 levels were associated with increased risk of heart failure in this latter study (7), perhaps because of an association of higher FGF23 with left ventricular hypertrophy (8,25,26). In light of these findings, it is intriguing that obesity, dyslipidemia, smoking, and hypertension were associated with higher FGF23 levels in this and prior studies (7,11,12). Because these factors are also associated with the development of heart failure, future studies should evaluate whether the association of FGF23 with mortality is primarily mediated by a link with adverse cardiac remodeling and whether classical pathogenic pathways underlying myocardial hypertrophy might help to elucidate responsible mechanisms.
Higher phosphorus intake was associated with higher FGF23 levels independently of age, creatinine, and other factors. Although this finding was not necessarily unexpected given that increased phosphorus consumption stimulates FGF23 secretion (1), it contrasts with the findings of a recent study that showed no association between FGF23 and estimated dietary phosphorus intake in nearly 4000 participants of the Chronic Renal Insufficiency Cohort (CRIC) Study (27). There are a number of potential reasons for this discrepancy. It is possible, for example, that phosphorus intake is more strongly associated with FGF23 levels in individuals with normal kidney function than in patients with CKD. Indeed, common metabolic disturbances related to kidney injury, such as lower GFR, higher serum phosphate levels, and higher PTH levels, are powerfully associated with higher FGF23 levels in CKD patients (27), potentially limiting the ability to detect more modest associations between phosphorus intake with FGF23 in CKD. It is also possible that differences in the dietary habits of the two populations may have played a role. The participants of the CRIC Study included a much larger proportion of individuals with low socioeconomic status than the participants of this study (28), all of whom were health professionals. Because less affluent individuals generally consume higher quantities of foods containing inorganic phosphorus additives incompletely captured by standard dietary surveys (29), this may have increased imprecision in the ascertainment of phosphorus intake in CRIC participants, further limiting the ability to detect an association of dietary phosphorus with FGF23 in the CRIC Study. Population-based studies that include individuals from across a wide spectrum of kidney function and socioeconomic status are needed to dissect these possibilities.
Our study had limitations. First, because we studied predominantly Caucasian men, it is unclear whether the associations we observed in this study can be extrapolated to more heterogeneous populations. Further studies will need to confirm our findings in more diverse populations. Second, kidney function was assessed via a single creatinine measurement obtained at baseline, which may have limited our ability to examine the effect of subtle decrements in kidney function on the associations described herein. Nevertheless, the results remained qualitatively the same in analyses excluding individuals with eGFR <60 ml/min per 1.73 m2, suggesting that decreased kidney function alone is unlikely to account for our findings. Third, we ascertained diet exposures from an FFQ that assessed average intake over the prior year, which may have reduced the magnitude of associations between phosphorus intake with FGF23. Fourth, we did not have measurements of 1,25-dihydoxyvitamin D, and so we could not examine its associations with FGF23 in this data set. Given that small physiologic studies showed that higher 1,25-dihydoxyvitamin D levels may mediate the association between higher PTH and higher FGF23 (30,31), future studies will need to examine these relationships in large population-based cohorts.
In summary, both dietary and nondietary factors were associated with higher FGF23 concentrations in community-living adults with mostly preserved kidney function. Given the growing body of literature demonstrating robust relationships between increased FGF23 and adverse health outcomes, future studies should examine whether traditional cardiovascular risk factors such as obesity, dyslipidemia, smoking, and hypertension may help explain these associations, particularly with respect to the consistent link between higher FGF23 and abnormalities of cardiac structure and function.
Disclosures
None.
Acknowledgments
The authors would like to thank Gary C. Curhan for his valuable review of this manuscript. This study was supported by Grants DK081673, HL092947, HL035464, and CA55075 from the National Institutes of Health.
Footnotes
Published online ahead of print. Publication date available at www.cjasn.org.
Access to UpToDate online is available for additional clinical information at www.cjasn.org.
See related editorial, “FGF23 Beyond Mineral Metabolism: A Bridge to Cardiovascular Disease,” on pages 2735–2737.
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