Is Baldness Dominant Or Recessive
To the Editor:
Common pattern baldness (androgenetic baldness) is the most common form of hair loss in humans. In Caucasians, normal male pilus loss, unremarkably known as "male pattern baldness" (MPB; MIM 109200), is noticeable in well-nigh twenty% of men aged xx, and increases steadily with historic period, so that a male in his 90s has a 90% chance of having some degree of MPB. In improver to being amid the most common natural conditions that make men cocky-conscious, recent studies indicate associations of MPB with: (ane) benign prostatic hyperplasia (MIM 600082; odds ratio (OR)=3.23; 95% confidence interval (CI): i.81–five.79) (
Militarist et al., 2000
- Hawk E.
- Breslow R.A.
- Graubard B.I.
Male person pattern baldness and clinical prostate cancer in the epidemiologic follow-up of the first National Health and Nutrition Examination Survey.
- PubMed
- Google Scholar
); (2) coronary heart disease (relative risk=1.36; 95% CI: 1.xi–ane.67) (
); (iii) hyperinsulinemia (OR=i.91; 95% CI: 1.02–3.56); and (4) insulin-resistance-associated disorders, such as obesity (MIM 601665; OR=2.90; 95% CI: 1.76–4.79), hypertension (MIM 145500; OR=two.09; 95% CI: 1.xiv–3.82), and dyslipidemia (OR=4.45; 95% CI: 1.74–eleven.34) (
). MBP is also a take a chance factor for clinical prostate cancer (MIM 176807; relative risk=one.50; 95% CI: 1.12–two.00) (
). Although it is a widely accustomed opinion that common baldness is an autosomal dominant phenotype in men and an autosomal recessive phenotype in women, or indeed that baldness is genetically influenced, it is based on surprisingly little empirical data. Here we grade MBP, in 476 monozygotic (MZ) and 408 dizygotic (DZ) male twin pairs aged betwixt 25 and 36 y and discover a heritability of 0.81 (95% CI: 0.77–0.85), thus confirming that genetic effects play a major role in the progression of common pilus loss.
Measures of pilus loss were obtained in the grade of an extensive semistructured telephone interview with respondent booklet, designed to assess physical, psychologic, and social manifestations of alcoholism and related disorders, conducted with 6265 twins born 1964 to 1971 from the volunteer-based Australian Twin Registry. All males (45% of the sample) were asked to rate their degree of hair loss, if any, using the Hamilton–Norwood Alopecia scale (
) (a standard classification scheme shown to take skilful exam–retest reliability) (
;
), which was printed in the respondent booklet (Figure one). This data collection scheme was validated in a study by
, which compared participant self-assessment hair loss confronting that determined by an independent trained observer in their research dispensary. Specifically, the self-assessed rating of score I in ix subjects was concurred by the trained observer in all only one private who received a score of II (p=0.317, Wilcoxon matched pairs signed rank examination), whereas no discrepancies with observer's scores were detected in 5 individuals with self-assessed scores ranging from Three to 7 (
).
Figure one Hamilton–Norwood standards for nomenclature of the most mutual types of MBP. Adapted from. Types I, II, 3, IV, V, VI, and 7 stand for the most common forms of MPB. Type IIIv has no more than front temporal hair loss than type Three, but has considerable pilus loss at the vertex. Blazon A variants (IIa, IIIa, Iva, and Va) have hair loss restricted to the anterior region, which somewhen recedes to equivalence with type VI (). Frequencies in our sample (2029 males aged 25–36 y) are: zero hair loss (61.ii%), I (half-dozen.five%), 2 (14.2%), IIa (2.9%), III (4.3%), IIIa (1.5%), IIIv (iii.8%), Iv (one.6%), IVa (ane.0%), V (0.eight%), Va (i.i%), Half-dozen (0.4%), and VII (0.five%).
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Data nerveless from 476 MZ and 408 DZ male pairs, plus 143 MZ and 154 DZ male individual twins (mean ages for the MZ and DZ twins were 30.three and thirty.v y, respectively) were analyzed using structural equation modeling, to guess parameters of a model that include additive genetic effects (A), nonadditive genetic effects (i.e., authorisation or epistasis) (D), shared or family environment (C), and random or unique surround (Due east) (
). In addition to the 12 Hamilton–Norwood categories, scoring individuals who answered "no" to the question "have you experienced hair loss?", as nil, resulted in a 13-point scale.
A major goal of the genetic analysis was to examination the multiple threshold model (
;
), which posits that unlike types of hair loss reflect different levels of severity on a unmarried dimension, rather than singled-out etiologies. These thresholds tin can be regarded as the z-value of the normal distribution that divides the surface area under the curve in such a way that it gives the right proportion of individuals in each (hair loss) group, thus reflecting the prevalence of each group (
). For each of the ii zygosity groups, the fit of a multiple threshold model was tested by calculating the polychoric correlation for the Hamilton–Norwood hair loss gradings, using POLYCORR (http://world wide web.ourworld.compuserve.com/homepages/jsuebersax/xpc.htm) or PRELIS ii.30 (
). The polychoric correlation, also termed the "correlation of liability", assumes that underlying the observed polychotomous distribution of pilus loss status there exists a continuous, commonly distributed latent liability (
). A χtwo goodness-of-fit test is used to examination whether the multiple threshold model provides a good fit to the observed data. Calculation of 95% CI for the polychoric correlations, the comparing of threshold values within twin pairs and beyond zygosity groups, and genetic model fitting by maximum likelihood univariate analysis of raw data were performed using the Mx program (
).
Multiple threshold model tests performed on the xiii categories, assuming equal thresholds for twin 1 and twin 2, indicated no significant divergence from normality in either MZ (χ2 155=117.94, p=0.99) or DZ twins (χ2 155=118.47, p=0.99), supporting a single liability dimension model of hair loss. As contingency tables using all 13 categories may be also sparse to yield a meaningful test of the multiple threshold model, however (e.yard., the χ2 statistic may non be asymptotically distributed), the MZ and DZ data were combined and the 13 score categories were complanate into the post-obit eight groups: group 1 (0, I, II, IIa; representing nonbaldness); group 2 (III); grouping 3 (IIIa); group 4 (IIIv, IV); grouping 5 (IVa); group 6 (5); group 7 (Va), and grouping eight (6, VII). Groups 2 to viii correspond pregnant cosmetic hair loss (
), while maximizing counts for vertex and recessive hair loss. Multiple threshold model tests performed on both the total eight×8 table and after combining frequencies in the two off-diagonal quadrants, besides indicated no pregnant departure from normality (χtwo 48=55.47, p=0.21 and χ2 18=19.58, p=0.36, respectively). These results strongly support a single liability dimension model of hair loss, with frontal recession not etiologically distinct from vertex balding.
After, a single liability dimension-threshold model was applied to our hair loss data, using the full distribution of ordered hair loss scores (0–I–II–IIa–Iii–IIIa–IIIv–IV–IVa–5–Va–Half dozen–Vii) as an ordered sequence reflecting the severity of hair loss (see Figure 2). No significant differences in threshold liability distributions were observed within twin pairs and across zygosity groups. The age corrected maximum likelihood (ML) twin pair polychoric correlation for hair loss gradings in MZ twin pairs (r=0.81; 95% CI: 0.77–0.85) was over twice as large as the DZ correlation (r=0.39; 95% CI: 0.28–0.49), indicating a stiff genetic event. Furthermore, genetic model fitting by ML univariate analysis of raw information using Mx (
) (Table I), indicated that an additive genetic and nonshared environmental (AE) model best explained individual differences in MPB, and that 81% of the total variance could be attributed to condiment genetic effects (i.east., 81% heritability, 95% CI: 77–85%).
Table I Genetic model fitting results using maximum likelihood raw data methods
| Goodness of fit | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Model | A | C | D | E | -2LL | d.f. | Δ-2LL | Δdf | p | vs. Model |
| ADE | 0.75 | 0.06 | 0.19 | 5485.58 | 2013 | |||||
| ACE | 0.81 | 0.00 | 0.nineteen | 5485.68 | 2013 | |||||
| AE a The AE model was institute to provide the nearly parsimonious fit to the information. | 0.81 | 0.19 | 5485.68 | 2014 | 0.09 | ane | 0.76 | ADE | ||
| CE | 0.62 | 0.38 | 5552.84 | 2014 | 67.sixteen | 1 | <0.001 | ACE | ||
Liability thresholds, computed using PRELIS ii.thirty (
), were utilized every bit starting values for the maximum likelihood univariate genetic analysis of raw data, performed using the Mx program (
). The correlation betwixt age and baldness was accounted for past simultaneously estimating and applying a single age displacement (normalized regression coefficient) (β=–0.06) to the threshold distribution. Offset, a fully "saturated" model (ADE or ACE) was tested to evaluate the statistical properties of the data, and so the event of dropping one of the parameters (A, C, D, or E) was examined past testing the respective deviation (Δ-2LL) for statistical significance.
a The AE model was institute to provide the most parsimonious fit to the data.
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Given the differences between some of the Hamilton–Norwood gradings are quite subtle, we re-analyzed our data using more than clear-cut (dichotomous) categories of hair loss. For these analyses, males with gradings of Iii, IIIa, IIIv, 4, IVa, V, Va, Half-dozen, or VII were classified equally bald, whereas males with gradings of 0, I, 2, or IIa were classified as nonbald. Analogous to the previous genetic analyses, an AE model best explained private differences in MPB, with eighty% of the total variance attributed to additive genetic effects (95% CI: 70–87%). Furthermore, the AE model best explained individual differences in MPB for dichotomized lucent vertex balding (0, I, or II vs. IIIv, IV, V, VI, or VII) and recessive balding (0, I, or II vs. IIIa, IVa, or Va) producing heritability estimates of 89% (95% CI: 75–95%) and 96% (95% CI: 87–99%), respectively. As predicted under the multiple threshold model, and reflected in their overlapping conviction intervals, the use of different grouping thresholds/schemes does not produce significantly unlike heritabilities.
Surprisingly, in that location is only 1 known extensive family study on androgenetic alopecia published (
). This study of pilus growth patterns in 22 families concluded that common baldness is an autosomal dominant phenotype in men and an autosomal recessive phenotype in women. Owing to a lack of details regarding examination methods and the practise of omitting symptom-free women in some pedigrees, however, the validity of these results remain controversial. Additionally, although the results from the 2 other known twin studies produced concordance rates of 100% and 92.3% for MZ, and 50% and 68.7% for DZ twins, they are far too small—including just three MZ and eight DZ male person pairs (
;
), and 65 MZ (42 male, 23 female) and 16 DZ (14 male, ii female) pairs (
Hayakawa et al., 1992
- Hayakawa K.
- Shimizu T.
- Ohba Y.
- et al.
Intrapair differences of concrete aging and longevity in identical twins.
- PubMed
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), respectively—to permit reliable conclusions.
Therefore, our results represent one of the first big-scale studies on the heritability of MBP and point that additive genetic effects play a major role in the progression of mutual pilus loss. Moreover, a recent study past
, which tested polymorphisms in the androgen receptor (AR) gene, found a StuI restriction site in 98.1% of 54 young (eighteen–30 y) baldheaded men (p=0.0005) and in 92.3% of 392 older (>fifty y) bald men (p=0.000004) compared with 76.6% of 107 nonbald (>50 y) men, suggesting that a polymorphism in or nigh AR (and in linkage disequilibrium with the AR StuI restriction site) is a contributing, but not sufficient, component of the genetic pre-disposition to MPB. Moreover, the AR gene is on chromosome Xq11.2–q12 and therefore could not explicate the like pilus loss patterns shared between father and sons, equally observed in an before study on the same population, where 32 of 54 bald cases (59.three%) had fathers with a greater degree of baldness, and only one of 65 sons of 50 nonbald controls had type Iii baldness or greater (
).
Hair loss similarities between father and son have also been observed in a report on the frequency of MPB in brothers of men having prematurely baldheaded fathers (66%) compared with brothers of men with unaffected fathers (46%;
;
). Further evidence confronting a unmarried and/or Ten-linked cistron of major effect comes from a written report by
Smith and Wells, 1964
- Smith M.A.
- Wells R.S.
Male person-type alopecia, alopecia areata, and normal pilus in women.
- Google Scholar
, which observed pilus loss in only 33% of the fathers of 18 women suffering from severe design alopecia (
). Additionally, a written report examining 410 men with premature baldness found evidence of a genetic influence from the father's side in 236 cases (
;
;
). Hence, other (autosomal) genes, possibly of large effect, remain to be plant.
It is worth noting that these heritabilities are based on a relatively young population—ranging in historic period from 25 to 36 with a mean of 30 y. Equally some of the nonbald subjects will inevitably develop balding—with the charge per unit of alopecia known to increase steadily with age—it is possible that heritability (A) will differ with age. For example, through the age-dependent expression of genes, and/or a modify in the body'southward resilience to the major furnishings of a genetic influence in early phases of life. Too, the accumulation of environmental influences (E) may play a larger part in older ages. Twin studies in older cohorts are required to investigate these possibilities.
The negative psychosocial effects associated with male person hair loss include decreased self-esteem, dissatisfaction with body image or advent, self-consciousness, perception of aging, and often emotional stress. Furthermore, these furnishings tend to be more pronounced in younger men (
). Certainly, MPB in itself has a considerable effect on the quality of life for many men. Because information technology is a clearly observable trait, notwithstanding, which generally precedes the diagnosis of benign prostatic hyperplasia and clinical prostate cancer by decades (
Militarist et al., 2000
- Hawk E.
- Breslow R.A.
- Graubard B.I.
Male design alopecia and clinical prostate cancer in the epidemiologic follow-up of the first National Health and Diet Exam Survey.
- PubMed
- Google Scholar
), genes influencing MPB may prove valuable in determining susceptibility to life-threatening prostatic disorders. Moreover, genes influencing MPB, may atomic number 82 to the identification of novel mechanisms, which may influence cardiovascular disease and/or insulin resistance.
ACKNOWLEDGMENTS
The authors wish to thank Dr David L Duffy for many helpful discussions. This research was supported in function by grants from NIAAA (United states of america) no. AA07535, and NHMRC (Australia) no. 941177 and no. 951023. DRN was supported in part by an NHMRC Peter Doherty Fellowship and NHMRC grant no. 241916.
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Article Info
Publication History
Accustomed: July 28, 2003
Received: July 14, 2003
Footnotes
Electronic Database Data: accession number and URL for information in this article are as follows: Online Mendelian Inheritance in Man (OMIM), http://www.ncbi.nlm.nih.gov/Omim/ (for MPB (MIM 109200), benign prostatic hyperplasia (MIM 600082), obesity (MIM 601665), hypertension (MIM 145500), and prostate cancer (MIM 176807)).
Identification
DOI: https://doi.org/10.1111/j.1523-1747.2003.12615.x
Copyright
© 2003 The Order for Investigative Dermatology, Inc. Published by Elsevier Inc.
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