TO THE EDITOR
Hair color, particularly red hair, is a variable phenotypic trait with high heritability. The melanocortin 1 receptor (MC1R) gene accounts for 73% of red hair heritability (Morgan et al. 2018). While 92% of red-haired individuals carry two MC1R variants, there is incomplete penetrance as most dual MC1R variants exhibit blonde or light brown hair (Morgan et al. 2018). Red hair is associated with sunburns, skin cancer, (Scherer and Kumar 2010) and pain sensitivity (Liem et al. 2005). Additionally, positive associations between red hair and cardiovascular disease and cancer in women, but not men, have been reported (Frost et al. 2017). We examined the Nurses’ Health Study (NHS) for associations in women between hair color and C-reactive protein (CRP), a marker of acute and chronic inflammation and cardiovascular risk (Ridker et al. 1997).
The NHS is a 1976 US cohort study of 121,700 female registered nurses aged 30–55 who provided written, informed consent. Follow-up details have been described previously (Bao et al. 2016). Between 1989 and 1990, 32,826 women provided blood specimens. There was no difference between these women and those who did not with respect to demographics, diet, and lifestyle (Bao et al. 2016). Procedures regarding blood collection have been reported previously (Bao et al. 2016). This study was approved by the Brigham and Women’s Hospital Institutional Review Board.
Hair color was ascertained in 1982 by asking: “What was the natural color of your hair at age 21?” with responses: “red”, “blonde”, “light brown”, “dark brown”, and “black”. CRP was measured using latex-enhanced immunoturbidimetric (Hang et al. 2019). Because multiple batches assessed CRP levels, lower detection limits and intra-assay coefficients of variation were examined (Table S1). We used a previously developed method to account for batch variability (Rosner et al. 2008) and used recalibrated levels (Hang et al. 2019).
In the NHS, demographic factors were collected at baseline and biennially. We included the following covariates: age, fasting status, body mass index (BMI), physical activity, smoking, alcohol consumption, Alternate Healthy Eating Index (AHEI), multivitamin use, aspirin/non-steroidal anti-inflammatory drug (NSAID) use, high blood pressure, elevated cholesterol, menopausal status, hormone replacement therapy use, and average July noon-time erythemal ultraviolet (UV) radiation. The latter was calculated using previously published methods (Vopham et al. 2016). We calculated cumulative average measurements from baseline to blood draw for continuous covariates, including BMI, physical activity, alcohol consumption, AHEI score, and UV radiation. Otherwise, we used covariate status at blood draw, when possible, or carried forward last available information.
We used the generalized extreme studentized deviate test to exclude outliers (Hang et al. 2019). To improve data normality, we used natural log transformed CRP levels. Age-adjusted and multivariable-adjusted linear regression analyses were conducted to examine the associations between four hair color groups (red – reference, blonde, light brown, and dark brown/black) and CRP levels. The results were presented as percentage differences in CRP versus the reference using the equation: [exp (β-coefficient) − 1] × 100%. Multiplicative interactions between hair color and covariates were tested. We also used multinomial logistic regression to examine for associations between hair color and CRP cardiovascular risk categories: Low (< 1.0 mg/mL), Intermediate (1.0 – 3.0 mg/L), and High (> 3.0 mg/L). Statistical analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC). Two-sided p-values < 0.05 were considered statistically significant.
This study included 11,141 participants with CRP levels (Figure S1). We excluded 1,746 participants (15.7%) with outlier CRP concentrations, erroneous records, missing data on hair color, non-white race, or a history of diabetes, cardiovascular disease, and/or cancer at blood draw, leaving 8,994 women (84.3%) remaining, among whom 390 (4.3%) had red hair (Table S2). The most common hair color was dark brown/black (45.1%). Mean CRP values were higher for women with red hair (3.7 mg/L, SD 3.9) compared to those with blonde (3.3 mg/L, SD 4.4), light brown (3.0 mg/mL, SD 4.0), or dark brown/black (3.2 mg/L, SD 4.3) hair.
In age-adjusted and multivariable-adjusted models, women with non-red hair had CRP levels 14.2 to 18.1% lower (p = 0.01 or less) and 10.9 to 14.1% lower (p = 0.04 or less), respectively, than red-haired women (Table 1). Interaction tests were non-significant for each covariate (p > 0.05). When examining CRP cardiovascular risk categories, we found, as expected, that non-red-haired women were less likely have high CRP levels (Table 2). Specifically, women with dark brown/black hair color had 0.67 lower odds of high CRP levels compared to red-haired women in both age-adjusted (95% CI: 0.52–0.87) and multivariable-adjusted (95% CI: 0.50–0.90) models.
Table 1.
Association between hair color and plasma CRP levels
| Hair Color | Red (Reference) | Blonde | Light brown | Dark brown or black | |||
|---|---|---|---|---|---|---|---|
| Percentage Difference in CRP (95% CI) | P-value | Percentage Difference in CRP (95% CI) | P-value | Percentage Difference in CRP (95% CI) | P-value | ||
| N | 390 | 1,095 | 3,451 | 4,058 | |||
| Model | 0 | −15.2 (−25.6, −3.2) | 0.01 | −18.1 (−27.3, −7.8) | 0.001 | −14.2 (−23.8, −3.5) | 0.01 |
| 1 | (reference) | ||||||
| Model | 0 | −12.7 (−22.5, −1.7) | 0.03 | −14.1 (−22.9, −4.3) | 0.006 | −10.9 (−19.9, −0.75) | 0.04 |
| 2 | (reference) | ||||||
Model 1 was adjusted for age at blood draw.
Model 2 was additionally adjusted for the following covariates: fasting status (yes or no), cumulative average levels of BMI (<18.5, 18.5–25, >30 kg/m2), cumulative average physical activity (<5.0, 5.0–11.5, 11.5–22, >=22 MET-hours/week), smoking status (‘never smoker’, ‘past smoker: unknown’, ‘past smoker: 1–14 cigs/day ’, ‘past smoker: 15–34 cigs/day ’, ‘past smoker: >=35 cigs/day’, ‘current smoker: unknown’, ‘current smoker: 1–14 cigs/day ’, ‘current smoker: 15–34 cigs/day ’, ‘current smoker: >=35 cigs/day’), cumulative average alcohol consumption (0, <0.15 0.15–7.5, 7.5–15, >=15.0 g/day), cumulative average AHEI dietary score (< 37.52, 37.52–43.46; 43.46–49.84, >= 49.84), average July noon-time erythemal UV radiation (quartiles), regular multivitamin use (yes or no), regular aspirin/NSAID use (yes or no), hypertension (yes or no), hypercholesterolemia (yes or no), menopausal status (pre-menopause, post-menopause, or dubious menopause), and postmenopausal hormone therapy (never, past, or current use).
Abbreviations: AHEI, Alternate Healthy Eating Index; BMI, body mass index; CI, confidence interval, CRP, C-reactive protein; MET, metabolic equivalent of task; NSAID, aspirin/nonsteroidal anti-inflammatory drug; UV, ultraviolet.
Table 2.
Odds Ratios (OR) for the association between CRP cardiovascular risk categories and hair color
| CRP Cardiovascular Risk Category | Low (CRP < 1.0 mg/L) (Reference) | Intermediate (CRP 1.0 – 3.0 mg/L) | High (CRP > 3.0 mg/L) | |||
|---|---|---|---|---|---|---|
| Hair Color | N | N | OR (95% CI) | N | OR (95% CI) | |
| Red (Reference) | Model 1 | 102 | 132 | 1 (reference) | 156 | 1 (reference) |
| Model 2 | 1 (reference) | 1 (reference) | ||||
| Blonde | Model 1 | 349 | 391 | 0.85 (0.63, 1.14) | 355 | 0.65 (0.48, 0.86) |
| Model 2 | 0.83 (0.61, 1.13) | 0.62 (0.45, 0.86) | ||||
| Light brown | Model 1 | 1,173 | 1,205 | 0.80 (0.61, 1.04) | 1,073 | 0.60 (0.46, 0.78) |
| Model 2 | 0.80 (0.60, 1.06) | 0.60 (0.45, 0.80) | ||||
| Dark brown or black | Model 1 | 1,311 | 1,426 | 0.85 (0.65, 1.12) | 1,321 | 0.67 (0.52, 0.87) |
| Model 2 | 0.86 (0.65, 1.14) | 0.67 (0.50, 0.90) | ||||
Model 1 was adjusted for age at blood draw.
Model 2 was additionally adjusted for the following covariates: fasting status (yes or no), cumulative average levels of BMI (<18.5, 18.5–25, >30 kg/m2), cumulative average physical activity (<5.0, 5.0–11.5, 11.5–22, >=22 MET-hours/week), smoking status (‘never smoker’, ‘past smoker: unknown’, ‘past smoker: 1–14 cigs/day ’, ‘past smoker: 15–34 cigs/day ’, ‘past smoker: >=35 cigs/day’, ‘current smoker: unknown’, ‘current smoker: 1–14 cigs/day ’, ’current smoker: 15–34 cigs/day ’, ‘current smoker: >=35 cigs/day’), cumulative average alcohol consumption (0, <0.15 0.15–7.5, 7.5–15, >=15.0 g/day), cumulative average AHEI dietary score (< 37.52, 37.5243.46; 43.46–49.84, >= 49.84), average July noon-time erythemal UV radiation (quartiles), regular multivitamin use (yes or no), regular aspirin/NSAID use (yes or no), hypertension (yes or no), hypercholesterolemia (yes or no), menopausal status (pre-menopause, post-menopause, or dubious menopause), and postmenopausal hormone therapy (never, past, or current use).
Abbreviations: AHEI, Alternate Healthy Eating Index; BMI, body mass index; CI, confidence interval; CRP, C-reactive protein; MET, metabolic equivalent of task; NSAID, aspirin/nonsteroidal anti-inflammatory drug; OR, odds ratio; UV, ultraviolet.
We found elevated CRP levels in red-haired women in the NHS. This finding could potentially explain a prior report of increased risks of cardiovascular disease and cancer in red-haired women (Frost et al. 2017). Although, we observed similar associations in the NHS between red hair and cardiovascular disease and cancer, they were not statistically significant (Tables S3 and S4).
In addition to its role in pigmentation, animal models suggest MC1R may influence inflammation via adaptive and innate immune responses (Nasti and Timares 2015). However, given the incomplete penetrance of MC1R in hair color, it is unclear if our findings are due to MC1R, another nearby gene, or other environmental factors. We examined MC1R genotypes and CRP levels among 6,509 participants in the NHS, but did not find an association and were limited by statistical power. A recent large genome-wide association study (GWAS) has identified two genes located near MC1R, ZFPM1 and FANCA, that are associated positively with CRP levels (Han et al. 2020). Genetic markers on these two genes have also been linked previously to hair color (Kichaev et al. 2019).
Our study has additional limitations. Hair color was identified by self-report, although in the NHS, self-reported variables have been validated (Colditz and Hankin son 2005), and hair color GWAS identified known pigmentation genes (Han et al. 2008). The generalizability of our study may be limited as the NHS included predominantly white, female, health professionals. Further studies are needed to validate our findings and understand the clinical significance and underlying mechanisms.
Supplementary Material
Acknowledgements:
We are indebted to the participants in the NHS for their dedication to this research. We thank the Channing Division of Network Medicine in Brigham and Women’s Hospital. We also thank the following state cancer registries for their help: Alabama, Arizona, Arkansas, California, Colorado, Connecticut, Delaware, Florida, Georgia, Idaho, Illinois, Indiana, Iowa, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Nebraska, New Hampshire, New Jersey, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, Tennessee, Texas, Virginia, Washington, and Wyoming. This work is supported by National Institutes of Health grants UM1 CA186107 and R01 CA49449. Dr. Hartman is supported by an American Skin Association Research Grant (120795). The authors assume full responsibility for analyses and interpretation of these data. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Funding sources: This study was supported by National Institutes of Health: UM1 CA186107 and R01 CA49449. Dr. Hartman is supported by an American Skin Association Research Grant (120795). Funding for Dr. Xin Li is partially provided by the Indiana University Grand Challenge Precision Health Initiative.
IRB approval status: This study was approved by the Brigham and Women’s Hospital Institutional Review Board (1999P011117).
Abbreviations Used:
- AEHI
Alternate Healthy Eating Index
- BMI
body mass index
- CRP
C-reactive protein
- MC1R
melanocortin 1 receptor
- MET
metabolic equivalent of task
- NHS
Nurses’ Health Study
- NSAID
non-steroidal anti-inflammatory drug
- US
United States
- UV
ultraviolet radiation
Footnotes
Conflict of Interest: The authors state no conflict of interest.
Data Availability: Data will be made available upon request. This study involved human subjects and to protect the privacy of study participants, data requests will be reviewed by the Nurses’ Health Study Steering Committee. Requests for data related to this JID publication should be directed to Dr. Xin Li at xl16@iu.edu.
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