Red Hair Color Is Associated with Elevated CRP Levels among US Women
2020; Elsevier BV; Volume: 141; Issue: 5 Linguagem: Inglês
10.1016/j.jid.2020.09.015
ISSN1523-1747
AutoresRebecca I. Hartman, Huilin Tang, Dong Hang, Mingyang Song, Hongmei Nan, Xin Li,
Tópico(s)Acne and Rosacea Treatments and Effects
ResumoHair color, especially red hair, is a variable phenotypic trait with high heritability. The MC1R gene accounts for 73% of red hair heritability (Morgan et al., 2018Morgan M.D. Pairo-Castineira E. Rawlik K. Canela-Xandri O. Rees J. Sims D. et al.Genome-wide study of hair colour in UK Biobank explains most of the SNP heritability.Nat Commun. 2018; 9: 5271Crossref PubMed Scopus (46) Google Scholar). Whereas 92% of red-haired individuals carry two MC1R variants, there is incomplete penetrance because most dual MC1R variants exhibit blonde or light brown hair (Morgan et al., 2018Morgan M.D. Pairo-Castineira E. Rawlik K. Canela-Xandri O. Rees J. Sims D. et al.Genome-wide study of hair colour in UK Biobank explains most of the SNP heritability.Nat Commun. 2018; 9: 5271Crossref PubMed Scopus (46) Google Scholar). Red hair is associated with sunburns, skin cancer, (Scherer and Kumar, 2010Scherer D. Kumar R. Genetics of pigmentation in skin cancer--a review.Mutat Res. 2010; 705: 141-153Crossref PubMed Scopus (138) Google Scholar), and pain sensitivity (Leim et al., 2005Leim E.B. Joiner T.V. Tsueda K. Sessler D.I. Increased sensitivity to thermal pain and reduced subcutaneous lidocaine efficacy in redheads.Anesthesiology. 2005; 102: 509-514Crossref PubMed Scopus (120) Google Scholar). In addition, positive associations between red hair and cardiovascular disease and cancer in women, but not in men, have been reported (Frost et al., 2017Frost P. Kleisner K. Flegr J. Health status by gender, hair color, and eye color: red-haired women are the most divergent.PLoS One. 2017; 12e0190238Crossref PubMed Scopus (15) Google Scholar). We examined the Nurses’ Health Study (NHS) for associations in women between hair color and CRP, a marker of acute and chronic inflammation and cardiovascular risk (Ridker et al., 1997Ridker P.M. Cushman M. Stampfer M.J. Tracy R.P. Hennekens C.H. Inflammation, aspirin, and the risk of cardiovascular disease in apparently healthy men.N Engl J Med. 1997; 336: 973-979Crossref PubMed Scopus (4799) Google Scholar). The NHS is a 1976 US cohort study of 121,700 female registered nurses aged 30–55 years who provided written, informed consent. Follow-up details have been described previously (Bao et al., 2016Bao Y. Bertoia M.L. Lenart E.B. Stampfer M.J. Willett W.C. Speizer F.E. et al.Origin, methods, and evolution of the three nurses’ health studies.Am J Public Health. 2016; 106: 1573-1581Crossref PubMed Scopus (197) Google Scholar). Between 1989 and 1990, a total of 32,826 women provided blood specimens. There was no difference between these women and those who did not provide blood specimens with respect to demographics, diet, and lifestyle (Bao et al., 2016Bao Y. Bertoia M.L. Lenart E.B. Stampfer M.J. Willett W.C. Speizer F.E. et al.Origin, methods, and evolution of the three nurses’ health studies.Am J Public Health. 2016; 106: 1573-1581Crossref PubMed Scopus (197) Google Scholar). Procedures regarding blood collection have been reported previously (Bao et al., 2016Bao Y. Bertoia M.L. Lenart E.B. Stampfer M.J. Willett W.C. Speizer F.E. et al.Origin, methods, and evolution of the three nurses’ health studies.Am J Public Health. 2016; 106: 1573-1581Crossref PubMed Scopus (197) Google Scholar). This study was approved by the Brigham and Women’s Hospital (Boston, MA) 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., 2019Hang D. Kværner A.S. Ma W. Hu Y. Tabung F.K. Nan H. et al.Coffee consumption and plasma biomarkers of metabolic and inflammatory pathways in US health professionals.Am J Clin Nutr. 2019; 109: 635-647Crossref PubMed Scopus (36) Google Scholar). Because multiple batches assessed CRP levels, lower detection limits and intra-assay coefficients of variation were examined (Supplementary Table S1). We used a previously developed method to account for batch variability (Rosner et al., 2008Rosner B. Cook N. Portman R. Daniels S. Falkner B. Determination of blood pressure percentiles in normal-weight children: some methodological issues.Am J Epidemiol. 2008; 167: 653-666Crossref PubMed Scopus (273) Google Scholar) and used recalibrated levels (Hang et al., 2019Hang D. Kværner A.S. Ma W. Hu Y. Tabung F.K. Nan H. et al.Coffee consumption and plasma biomarkers of metabolic and inflammatory pathways in US health professionals.Am J Clin Nutr. 2019; 109: 635-647Crossref PubMed Scopus (36) Google Scholar). In the NHS, demographic factors were collected at baseline and biennially. We included the following covariates: age, fasting status, body mass index, physical activity, smoking, alcohol consumption, Alternate Healthy Eating Index, multivitamin use, aspirin or non-steroidal anti-inflammatory drug use, high blood pressure, elevated cholesterol, menopausal status, hormone replacement therapy use, and average July noon-time erythemal UVR. Average July noon-time erythemal UVR was calculated using previously published methods (VoPham et al., 2016VoPham T. Hart J.E. Bertrand K.A. Sun Z. Tamimi R.M. Laden F. Spatiotemporal exposure modeling of ambient erythemal ultraviolet radiation.Environ Health. 2016; 15: 111Crossref PubMed Scopus (25) Google Scholar). We calculated cumulative average measurements from baseline to blood draw for continuous covariates, including body mass index, physical activity, alcohol consumption, Alternate Healthy Eating Index score, and UVR. Otherwise, we used covariate status at blood draw, when possible, or carried forward the last available information. We used the generalized extreme studentized deviate test to exclude outliers (Hang et al., 2019Hang D. Kværner A.S. Ma W. Hu Y. Tabung F.K. Nan H. et al.Coffee consumption and plasma biomarkers of metabolic and inflammatory pathways in US health professionals.Am J Clin Nutr. 2019; 109: 635-647Crossref PubMed Scopus (36) Google Scholar). 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 and/or 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 ( 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 (Supplementary 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 (Supplementary Table S2). The most common hair color was dark brown and/or black (45.1%). Mean CRP values were higher for women with red hair (3.7 mg/l, SD = 3.9) than for those with blonde (3.3 mg/l, SD = 4.4), light brown (3.0 mg/ml, SD = 4.0), or dark brown and/or black (3.2 mg/l, SD = 4.3) hair. In age-adjusted and multivariable-adjusted models, women with non-red hair had CRP levels of 14.2–18.1% lower (P ≤ 0.01) and 10.9–14.1% lower (P ≤ 0.04), respectively, than those of red-haired women (Table 1). Interaction tests were nonsignificant for each covariate (P > 0.05). When examining CRP cardiovascular risk categories, we found, as expected, that non‒red-haired women were less likely to have high CRP levels (Table 2). Specifically, women with dark brown and/or black hair color had 0.67 lower odds of high CRP levels than red-haired women in both age-adjusted (95% confidence interval = 0.52–0.87) and multivariable-adjusted (95% confidence interval = 0.50–0.90) models.Table 1Association between Hair Color and Plasma CRP LevelsHair ColorRed(Reference)BlondeLight BrownDark Brown or BlackPercentage Difference in CRP (95% CI)P-valuePercentage Difference in CRP (95% CI)P-valuePercentage Difference in CRP (95% CI)P-valuen3901,0953,4514,058Model 11Model 1 was adjusted for age at blood draw.0 (reference)−15.2 (−25.6 to −3.2)0.01−18.1 (−27.3 to −7.8)0.001−14.2 (−23.8 to −3.5)0.01Model 22Model 2 was additionally adjusted for the following covariates: fasting status (yes or no), cumulative average levels of BMI ( 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 UVR (quartiles), regular multivitamin use (yes or no), regular aspirin and/or NSAID use (yes or no), hypertension (yes or no), hypercholesterolemia (yes or no), menopausal status (premenopause, postmenopause, or dubious menopause), and postmenopausal hormone therapy (never, past, or current use).0 (reference)−12.7 (−22.5 to −1.7)0.03−14.1 (−22.9 to −4.3)0.006−10.9 (−19.9 to −0.75)0.04Abbreviations: AHEI, Alternate Healthy Eating Index; BMI, body mass index; CI, confidence interval; cig, cigarette; MET, metabolic equivalent of task; NSAID, nonsteroidal anti-inflammatory drug.1 Model 1 was adjusted for age at blood draw.2 Model 2 was additionally adjusted for the following covariates: fasting status (yes or no), cumulative average levels of BMI ( 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 UVR (quartiles), regular multivitamin use (yes or no), regular aspirin and/or NSAID use (yes or no), hypertension (yes or no), hypercholesterolemia (yes or no), menopausal status (premenopause, postmenopause, or dubious menopause), and postmenopausal hormone therapy (never, past, or current use). Open table in a new tab Table 2OR for the Association between CRP Cardiovascular Risk Categories and Hair ColorCRP Cardiovascular Risk CategoryHair ColorLow (CRP of 3.0 mg/l)nOR (95% CI)nOR (95% CI)Red (reference)Model 11Model 1 was adjusted for age at blood draw.1021321 (reference)1561 (reference)Model 22Model 2 was additionally adjusted for the following covariates: fasting status (yes or no), cumulative average levels of BMI ( 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 UVR (quartiles), regular multivitamin use (yes or no), regular aspirin and/or NSAID use (yes or no), hypertension (yes or no), hypercholesterolemia (yes or no), menopausal status (premenopause, postmenopause, or dubious menopause), and postmenopausal hormone therapy (never, past, or current use).1 (reference)1 (reference)BlondeModel 11Model 1 was adjusted for age at blood draw.3493910.85 (0.63–1.14)3550.65 (0.48–0.86)Model 22Model 2 was additionally adjusted for the following covariates: fasting status (yes or no), cumulative average levels of BMI ( 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 UVR (quartiles), regular multivitamin use (yes or no), regular aspirin and/or NSAID use (yes or no), hypertension (yes or no), hypercholesterolemia (yes or no), menopausal status (premenopause, postmenopause, or dubious menopause), and postmenopausal hormone therapy (never, past, or current use).0.83 (0.61–1.13)0.62 (0.45–0.86)Light brownModel 11Model 1 was adjusted for age at blood draw.1,1731,2050.80 (0.61–1.04)1,0730.60 (0.46–0.78)Model 22Model 2 was additionally adjusted for the following covariates: fasting status (yes or no), cumulative average levels of BMI ( 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 UVR (quartiles), regular multivitamin use (yes or no), regular aspirin and/or NSAID use (yes or no), hypertension (yes or no), hypercholesterolemia (yes or no), menopausal status (premenopause, postmenopause, or dubious menopause), and postmenopausal hormone therapy (never, past, or current use).0.80 (0.60–1.06)0.60 (0.45–0.80)Dark brown or blackModel 11Model 1 was adjusted for age at blood draw.1,3111,4260.85 (0.65–1.12)1,3210.67 (0.52–0.87)Model 22Model 2 was additionally adjusted for the following covariates: fasting status (yes or no), cumulative average levels of BMI ( 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 UVR (quartiles), regular multivitamin use (yes or no), regular aspirin and/or NSAID use (yes or no), hypertension (yes or no), hypercholesterolemia (yes or no), menopausal status (premenopause, postmenopause, or dubious menopause), and postmenopausal hormone therapy (never, past, or current use).0.86 (0.65–1.14)0.67 (0.50–0.90)Abbreviations: AHEI, Alternate Healthy Eating Index; BMI, body mass index; CI, confidence interval; cig, cigarette; MET, metabolic equivalent of task; NSAID, nonsteroidal anti-inflammatory drug.1 Model 1 was adjusted for age at blood draw.2 Model 2 was additionally adjusted for the following covariates: fasting status (yes or no), cumulative average levels of BMI ( 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 UVR (quartiles), regular multivitamin use (yes or no), regular aspirin and/or NSAID use (yes or no), hypertension (yes or no), hypercholesterolemia (yes or no), menopausal status (premenopause, postmenopause, or dubious menopause), and postmenopausal hormone therapy (never, past, or current use). Open table in a new tab Abbreviations: AHEI, Alternate Healthy Eating Index; BMI, body mass index; CI, confidence interval; cig, cigarette; MET, metabolic equivalent of task; NSAID, nonsteroidal anti-inflammatory drug. Abbreviations: AHEI, Alternate Healthy Eating Index; BMI, body mass index; CI, confidence interval; cig, cigarette; MET, metabolic equivalent of task; NSAID, nonsteroidal anti-inflammatory drug. We found elevated CRP levels in red-haired women in the NHS. This finding could potentially explain a previous report of increased risks of cardiovascular disease and cancer in red-haired women (Frost et al., 2017Frost P. Kleisner K. Flegr J. Health status by gender, hair color, and eye color: red-haired women are the most divergent.PLoS One. 2017; 12e0190238Crossref PubMed Scopus (15) Google Scholar). Although we observed similar associations in the NHS between red hair and cardiovascular disease and cancer, they were not statistically significant (Supplementary Tables S3 and S4). In addition to its role in pigmentation, animal models suggest that MC1R may influence inflammation through adaptive and innate immune responses (Nasti and Timares, 2015Nasti T.H. Timares L. MC1R, eumelanin and pheomelanin: their role in determining the susceptibility to skin cancer.Photochem Photobiol. 2015; 91: 188-200Crossref PubMed Scopus (94) Google Scholar). However, given the incomplete penetrance of MC1R in hair color, it is unclear whether 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 GWAS has identified two genes located near MC1R, ZFPM1, and FANCA, which are associated positively with CRP levels (Han et al., 2020Han X. Ong J.S. An J. Hewitt A.W. Gharahkhani P. MacGregor S. Using Mendelian randomization to evaluate the causal relationship between serum C-reactive protein levels and age-related macular degeneration.Eur J Epidemiol. 2020; 35: 139-146Crossref PubMed Scopus (16) Google Scholar). Genetic markers on these two genes have also been linked previously to hair color (Kichaev et al., 2019Kichaev G. Bhatia G. Loh P.R. Gazal S. Burch K. Freund M.K. et al.Leveraging polygenic functional enrichment to improve GWAS power.Am J Hum Genet. 2019; 104: 65-75Abstract Full Text Full Text PDF PubMed Scopus (284) Google Scholar). Our study has additional limitations. Hair color was identified by self-report, although in the NHS, self-reported variables have been validated (Colditz and Hankinson, 2005Colditz G.A. Hankinson S.E. The nurses’ health study: lifestyle and health among women.Nat Rev Cancer. 2005; 5: 388-396Crossref PubMed Scopus (436) Google Scholar), and hair color GWAS identified known pigmentation genes (Han et al., 2008Han J. Kraft P. Nan H. Guo Q. Chen C. Qureshi A. et al.A genome-wide association study identifies novel alleles associated with hair color and skin pigmentation.PLoS Genet. 2008; 4e1000074Crossref PubMed Scopus (360) Google Scholar). The generalizability of our study may be limited because the NHS included predominantly white, female health professionals. Further studies are needed to validate our findings and understand the clinical significance and underlying mechanisms. 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 Journal of Investigative Dermatology publication should be directed to XL at [email protected] . Rebecca I. Hartman: http://orcid.org/0000-0001-5559-9100 Huilin Tang: http://orcid.org/0000-0002-5814-6657 Dong Hang: http://orcid.org/0000-0001-6944-0459 Mingyang Song: http://orcid.org/0000-0002-1324-0316 Hongmei Nan: http://orcid.org/0000-0002-9957-616X Xin Li: http://orcid.org/0000-0002-0135-8800 The authors state no conflicts of interest. We are indebted to the participants in the Nurses’ Health Study for their dedication to this research. We thank the Channing Division of Network Medicine in Brigham and Women’s Hospital (Boston, MA). 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 the National Institutes of Health grants UM1 CA186107 and R01 CA49449. RIH is supported by an American Skin Association Research grant (120795). The authors assume full responsibility for the analyses and interpretation of these data. The content of this paper is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. This study was approved by the Brigham and Women’s Hospital Institutional Review Board (1999P011117). Conceptualization: RIH; Data Curation: HT, DH, MS; Formal Analysis: HT, XL; Investigation: XL; Methodology: RIH, XL; Project Administration: XL; Resources: MS, XL; Supervision: XL; Visualization: RIH, HT; Writing - Original Draft Preparation: RIH; Writing - Review and Editing: HT, MS, HN, XL Download .pdf (.12 MB) Help with pdf files Supplementary Material
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