Evaluation of DNA variants associated with androgenetic alopecia and their potential to predict male pattern baldness

Loss of the Y Chromosome: A Review of Molecular Mechanisms, Age Inference, and Implications for Men's Health

Until a few years ago, it was believed that the gradual mosaic loss of the Y chromosome (mLOY) was a normal age-related process. However, it is now known that mLOY is associated with a wide variety of pathologies in men, such as cardiovascular diseases, neurodegenerative disorders, and many types of cancer. Nevertheless, the mechanisms that generate mLOY in men have not been studied so far. This task is of great importance because it will allow focusing on possible methods of prophylaxis or therapy for diseases associated with mLOY. On the other hand, it would allow better understanding of mLOY as a possible marker for inferring the age of male samples in cases of human identification. Due to the above, in this work, a comprehensive review of the literature was conducted, presenting the most relevant information on the possible molecular mechanisms by which mLOY is generated, as well as its implications for men's health and its possible use as a marker to infer age.

Analysis of epigenetic clocks links yoga, sleep, education, reduced meat intake, coffee, and a SOCS2 gene variant to slower epigenetic aging

DNA methylation (DNAm) clocks hold promise for measuring biological age, useful for guiding clinical interventions and forensic identification. This study compared the commonly used DNAm clocks, using DNA methylation and SNP data generated from nearly 1000 human blood or buccal swab samples. We evaluated different preprocessing methods for age estimation, investigated the association of epigenetic age acceleration (EAA) with various lifestyle and sociodemographic factors, and undertook a series of novel genome-wide association analyses for different EAA measures to find associated genetic variants. Our results highlighted the Skin&Blood clock with ssNoob normalization as the most accurate predictor of chronological age. We provided novel evidence for an association between the practice of yoga and a reduction in the pace of aging (DunedinPACE). Increased sleep and physical activity were associated with lower mortality risk score (MRS) in our dataset. University degree, vegetable consumption, and coffee intake were associated with reduced levels of epigenetic aging, whereas smoking, higher BMI, meat consumption, and manual occupation correlated well with faster epigenetic aging, with FitAge, GrimAge, and DunedinPACE clocks showing the most robust associations. In addition, we found a novel association signal for SOCS2 rs73218878 (p = 2.87 × 10-8) and accelerated GrimAge. Our study emphasizes the importance of an optimized DNAm analysis workflow for accurate estimation of epigenetic age, which may influence downstream analyses. The results support the influence of genetic background on EAA. The associated SOCS2 is a member of the suppressor of cytokine signaling family known for its role in human longevity. The reported association between various risk factors and EAA has practical implications for the development of health programs to improve quality of life and reduce premature mortality associated with age-related diseases.

A missense mutation in Lama3 causes androgen alopecia

Hair loss disorders such as androgenetic alopecia have caused serious disturbances to normal human life. Animal models play an important role in exploring pathogenesis of disease and evaluating new therapies. NIH hairless mice are a spontaneous hairless mouse discovered and bred in our laboratory. In this study, we resequenced the genomes of NIH normal mice and NIH hairless mice and obtained 3,575,560 high-quality, plausible SNP loci and 995,475 InDels. The Euclidean distance algorithm was used to assess the association of SNP loci with the hairless phenotype, at a threshold of 0.62. Two regions of chromosome 18 having the highest association with the phenotype contained 345 genes with a total length of 13.98 Mb. The same algorithm was used to assess the association of InDels with the hairless phenotype at a threshold of 0.54 and revealed a region of 25.45 Mb in length, containing 518 genes. The mutation candidate gene Lama3 (NM_010680.2: c.652C>T; NP_034810.1: p. Arg217Cys) was selected based on the results of functional gene analysis and mutation prediction screening. Lama3 (R217C) mutant mice were further constructed using CRISPR/Cas9 technology, and the relationship between Lama3 point mutations and the hairless phenotype were clarified by phenotypic observation. The results showed that male Lama3 point mutation mice started to lose hair on the 80th day after birth, and the hair loss area gradually expanded over time. H&E staining of skin sections showed that the point mutation mice had increased sebaceous glands in the dermis and missing hair follicle structure (i.e., typical symptoms of androgenetic alopecia). This study is a good extension of the current body of knowledge about the function of Lama3, and the constructed Lama3 (R217C) mutant mice may be a good animal model for studying androgenetic alopecia.

Phenotype predictions of two-person mixture using single cell analysis

Over a decade after the publication of the first forensic DNA phenotyping (FDP) studies, DNA-based appearance predictions are now becoming a reality in routine crime scene investigations. The significant number of publications dedicated to the subject of FDP clearly demonstrates a sustained interest and a strong need for further method development. However, the implementation of FDP in routine work still encounters obstacles, and one of these challenges is making phenotype predictions from DNA mixtures. In this study, we examined single-cell sequencing as a potential tool to enable reliable phenotyping of contributors within mixtures. Two mock mixtures, each containing two contributors with similar and different physical appearances, were analyzed using two different workflows. In the first workflow, the mixtures were sequenced using the Ion AmpliSeq™ PhenoTrivium Panel, which includes 41 HIrisPlex-S (HPS) markers. Subsequently, the genotypes were analyzed using the HPS Deconvolution Tool to predict the phenotypes of both contributors. The second workflow involved the introduction of single-cell separation and collection using the DEPArray™ PLUS System. Two different PhenoTrivium amplification protocols were tested, and the phenotype predictions from single cells were compared with the results obtained using the HPS Tool. Our results suggest that the approach presented here allows for the obtainment of nearly complete HIrisPlex-S profiles with accurate genotypes and reliable phenotype predictions from single cells. This method proves successful in deconvoluting mixtures submitted to forensic DNA phenotyping.

Evaluation of loci to predict ear morphology using two SNaPshot assays

Human ear morphology prediction with SNP-based genotypes is growing in forensic DNA phenotyping and is scarcely explored in Pakistan as a part of EVCs (externally visible characteristics). The ear morphology prediction assays with 21 SNPs were assessed for their potential utility in forensic identification of population. The SNaPshot™ multiplex chemistries, capillary electrophoresis methods and GeneMapper™ software were used for obtaining genotypic data. A total of 33 ear phenotypes were categorized with digital photographs of 300 volunteers. SHEsis software was applied to make LD plot. Ordinal and multinomial logistic regression was implemented for association testing. Multinomial logistic regression was executed to construct the prediction model in 90% training and 10% testing subjects. Several influential SNPs for ear phenotypic variation were found in association testing. The model based on genetic markers predicted ear phenotypes with moderate to good predictive accuracies demonstrated with the area under curve (AUC), sensitivity and specificity of predicted phenotypes. As an additional EVC, the estimated ear phenotypic profiles have the possibility of determining the human ear morphology differences in unknown biological samples found in crimes that do not result in a criminal database hit. Furthermore, this can help in facial reconstruction and act as an investigational lead.

Evaluation of facial hair-associated SNPs: a pilot study on male Pakistani Punjabi population

Variation in facial hair is one of the most conspicuous features of facial appearance, particularly in South Asia and Middle East countries. A genome-wide association study in Latin Americans has identified multiple genetic variants at distinct loci being associated with facial hair traits including eyebrow thickness, beard thickness, and monobrow. In this pilot study, we have evaluated 16 SNPs associated with facial hair traits in 58 male individuals from the Punjabi population of Pakistan. In our sample, rs365060 in EDAR and rs12597422 in FTO showed significant association with monobrow, rs6684877 in MACF1 showed significant association with eyebrow thickness, and two SNPs in LOC105379031 (rs9654415 and rs7702331) showed significant association with beard thickness. Our results also suggest that genetic association may vary between ethnic groups and geographic regions. Although more data are needed to validate our results, our findings are of value in forensic molecular photofitting research in Pakistan.

Male-pattern hair loss: Comprehensive identification of the associated genes as a basis for understanding pathophysiology

Male-pattern hair loss (MPHL) is a highly heritable and prevalent condition that is characterized by progressive hair loss from the frontotemporal and vertex scalp. This androgen-dependent hair loss may commence during puberty, and up to 80 % of European men experience some degree of MPHL during their lifetime. Current treatment options for MPHL have limited efficacy, and improved understanding of the underlying biological causes is required to facilitate novel therapeutic approaches. To date, molecular genetic studies have identified 389 associated genomic regions, have implicated numerous genes in these regions, and suggested pathways that are likely to contribute to key pathophysiological mechanisms in MPHL. This review provides an overview of the current status of MPHL genetic research. We discuss the most significant achievements, current challenges, and anticipated developments in the field, as well as their potential to advance our understanding of hair (loss) biology, and to improve hair loss prediction and treatment.

Recent advances in Forensic DNA Phenotyping of appearance, ancestry and age

Forensic DNA Phenotyping (FDP) comprises the prediction of a person's externally visible characteristics regarding appearance, biogeographic ancestry and age from DNA of crime scene samples, to provide investigative leads to help find unknown perpetrators that cannot be identified with forensic STR-profiling. In recent years, FDP has advanced considerably in all of its three components, which we summarize in this review article. Appearance prediction from DNA has broadened beyond eye, hair and skin color to additionally comprise other traits such as eyebrow color, freckles, hair structure, hair loss in men, and tall stature. Biogeographic ancestry inference from DNA has progressed from continental ancestry to sub-continental ancestry detection and the resolving of co-ancestry patterns in genetically admixed individuals. Age estimation from DNA has widened beyond blood to more somatic tissues such as saliva and bones as well as new markers and tools for semen. Technological progress has allowed forensically suitable DNA technology with largely increased multiplex capacity for the simultaneous analysis of hundreds of DNA predictors with targeted massively parallel sequencing (MPS). Forensically validated MPS-based FDP tools for predicting from crime scene DNA i) several appearance traits, ii) multi-regional ancestry, iii) several appearance traits together with multi-regional ancestry, and iv) age from different tissue types, are already available. Despite recent advances that will likely increase the impact of FDP in criminal casework in the near future, moving reliable appearance, ancestry and age prediction from crime scene DNA to the level of detail and accuracy police investigators may desire, requires further intensified scientific research together with technical developments and forensic validations as well as the necessary funding.

Genetic prediction of male pattern baldness based on large independent datasets

Genetic prediction of male pattern baldness (MPB) is important in science and society. Previous genetic MPB prediction models were limited by sparse marker coverage, small sample size, and/or data dependency in the different analytical steps. Here, we present novel models for genetic prediction of MPB based on a large set of markers and large independent subsample sets drawn among 187,435 European subjects. We selected 117 SNP predictors within 85 distinct loci from a list of 270 previously MPB-associated SNPs in 55,573 males of the UK Biobank Study (UKBB). Based on these 117 SNPs with and without age as additional predictor, we trained, by use of different methods, prediction models in a non-overlapping subset of 104,694 UKBB males and tested them in a non-overlapping subset of 26,177 UKBB males. Estimates of prediction accuracy were similar between methods with AUC ranges of 0.725-0.728 for severe, 0.631-0.635 for moderate, 0.598-0.602 for slight, and 0.708-0.711 for no hair loss with age, and slightly lower without, while prediction of any versus no hair loss gave 0.690-0.711 with age and slightly lower without. External validation in an early-onset enriched MPB dataset from the Bonn Study (N = 991) showed improved prediction accuracy without considering age such as AUC of 0.830 for no vs. any hair loss. Because of the large number of markers and the large independent datasets used for the different analytical steps, the newly presented genetic prediction models are the most reliable ones currently available for MPB or any other human appearance trait.

Possible relationship between poor skin disorders prognosis and serum zinc level: A narrative review

Zinc is a trace nutrient essential for the normal growth and development of human body. The main aim was to evaluate the significant association between measured zinc status in relation to different skin disorders and their severity. PubMed®, Google® Scholar™ and Cochrane© Reviews databases were searched for studies from January 2017 to June 2021, using the terms; zinc serum levels, zinc plasma levels and different dermatosis in the review, only human studies in English language were reviewed and the studies designs were controlled, cross sectional, observational and analytic types. A total of forty-eight research studies were included in this review. All studies have evaluated serum zinc in skin diseases including psoriasis, atopic dermatitis, pityriasis alba, androgenetic alopecia areata, telogen effluvium, vitiligo, melasma, acne, seborrheic dermatitis and hidradenitis suppuritiva. It was found that 33 studies had validated statistically significant differences in serum zinc levels between patients and controls. There is a predominance of low serum zinc levels in all the dermatoses reviewed. The clinical significance of this finding highlights the possible value, and need to investigate, the use of Zinc supplementation as an adjuvant therapy in the management of chronic inflammatory and autoimmune skin diseases proven to manifest altered zinc levels.

The first broad replication study of SNPs and a pilot genome-wide association study for androgenetic alopecia in Asian populations

BACKGROUND

Many candidate genes for androgenetic alopecia (AGA) have been identified in studies of the Caucasians and some Asian populations.

AIMS

This study aimed to confirm the known susceptibility genes reported in previous studies and find additional candidate genes for high-risk individuals for AGA in Korean population.

PATIENTS/METHODS

We recapitulated the previously reported SNPs and identified the novel Korean AGA risk genetic variants using a Korean hospital-based AGA case and control samples. The population was consisting of 494 individuals (275 AGA cases and 146 controls). Using the 800 K SNPs of precision medical research array (PMRA SNP microarray chip) and imputation-based SNPs, 12 previous GWAS reports for AGA and a total of 62 160 SNPs were examined in our study samples. Also, we conducted the genome-wide association study (GWAS) by the logistic regression analyses for AGA cases and controls with controlling the age as the covariates.

RESULTS

Among the 62 160 SNPs, a total of 1143 SNPs in 76 gene regions showed weak replication tendency with the p-values <0.05 and same direction of effects. Additionally, the GWAS results showed 110 SNPs in 13 independent regions with the suggestive p-values <1.00 × 10^-5 . The most significantly replicated SNP resided on chromosome 20, which were similar to other AGA replication studies including Chinese study. The GWAS identified two SNPs (rs11010734 and rs2420640) increasing the risk for AGA in our study population.

CONCLUSIONS

Our study would be a reference of the non-European studies to better understand AGA in different populations and ancestral contexts.

The Progressive Loss Risk Scale for Hair Restoration Surgery

BACKGROUND

Limited information exists on the long-term risks to individuals undergoing procedures in hair restoration surgery. The short-term risks are well known and similar to other procedures in dermatologic surgery. The long-term risks of hair restoration surgery are seldom discussed between the physician and patient.

OBJECTIVE

The author sought to describe a classification system that can be used as a communication tool between physicians and patients to define the long-term risk involved with hair restoration surgery.

METHODS

The Progressive Loss (PL) Scale is an attempt at assessing the cosmesis because of future hair loss following a hair transplant procedure. The PL Risk Scale has designated 5 levels, 1 to 5, with each ascending level representing a higher level of risk. The PL Risk Scale can be assigned to an individual at the time of the assessment for hair restoration surgery.

RESULTS

Each patient can be assigned a risk level based on how future hair loss may affect the overall cosmetic result of their hair transplant. This risk is dependent on age, and specific for the area to be transplanted. The younger the age of the patient, the higher the risk. The larger the area to be transplanted, the higher the risk. It is not a static scale, because it will be affected by age, donor area, location of transplantation, and other mitigating factors.

CONCLUSION

Pattern baldness in men and women is progressive and unrelenting. The dichotomy of hair restoration surgery is that a satisfactory short-term outcome can evolve to disappointing results because of progressive hair loss. The PL Risk Scale can be assigned to every individual undergoing a hair restoration procedure. This scale assignment will convey to the patient their lifetime risk associated with any given surgical hair restoration procedure for that age and the specific area to be restored.

Predicting Physical Appearance from DNA Data-Towards Genomic Solutions

The idea of forensic DNA intelligence is to extract from genomic data any information that can help guide the investigation. The clues to the externally visible phenotype are of particular practical importance. The high heritability of the physical phenotype suggests that genetic data can be easily predicted, but this has only become possible with less polygenic traits. The forensic community has developed DNA-based predictive tools by employing a limited number of the most important markers analysed with targeted massive parallel sequencing. The complexity of the genetics of many other appearance phenotypes requires big data coupled with sophisticated machine learning methods to develop accurate genomic predictors. A significant challenge in developing universal genomic predictive methods will be the collection of sufficiently large data sets. These should be created using whole-genome sequencing technology to enable the identification of rare DNA variants implicated in phenotype determination. It is worth noting that the correctness of the forensic sketch generated from the DNA data depends on the inclusion of an age factor. This, however, can be predicted by analysing epigenetic data. An important limitation preventing whole-genome approaches from being commonly used in forensics is the slow progress in the development and implementation of high-throughput, low DNA input sequencing technologies. The example of palaeoanthropology suggests that such methods may possibly be developed in forensics.

DNA methylation-based age clocks: From age prediction to age reversion

Aging as an irretrievable occurrence throughout the entire life is characterized by a progressive decline in physiological functionality and enhanced disease vulnerability. Numerous studies have demonstrated that epigenetic modifications, particularly DNA methylation (DNAm), correlate with aging and age-related diseases. Several investigations have attempted to predict chronological age using the age-related alterations in the DNAm of certain CpG sites. Here we categorize different studies that tracked the aging process in the DNAm landscape to show how epigenetic age clocks evolved from a chronological age estimator to an indicator of lifespan and healthspan. We also describe the health and disease predictive potential of estimated epigenetic age acceleration regarding different clinical conditions and lifestyle factors. Considering the revealed age-related epigenetic changes, the recent age-reprogramming strategies are discussed which are promising methods for resetting the aging clocks.

Testing the impact of trait prevalence priors in Bayesian-based genetic prediction modeling of human appearance traits

The prediction of appearance traits by use of solely genetic information has become an established approach and a number of statistical prediction models have already been developed for this purpose. However, given limited knowledge on appearance genetics, currently available models are incomplete and do not include all causal genetic variants as predictors. Therefore such prediction models may benefit from the inclusion of additional information that acts as a proxy for this unknown genetic background. Use of priors, possibly informed by trait category prevalence values in biogeographic ancestry groups, in a Bayesian framework may thus improve the prediction accuracy of previously predicted externally visible characteristics, but has not been investigated as of yet. In this study, we assessed the impact of using trait prevalence-informed priors on the prediction performance in Bayesian models for eye, hair and skin color as well as hair structure and freckles in comparison to the respective prior-free models. Those prior-free models were either similarly defined either very close to the already established ones by using a reduced predictive marker set. However, these differences in the number of the predictive markers should not affect significantly our main outcomes. We observed that such priors often had a strong effect on the prediction performance, but to varying degrees between different traits and also different trait categories, with some categories barely showing an effect. While we found potential for improving the prediction accuracy of many of the appearance trait categories tested by using priors, our analyses also showed that misspecification of those prior values often severely diminished the accuracy compared to the respective prior-free approach. This emphasizes the importance of accurate specification of prevalence-informed priors in Bayesian prediction modeling of appearance traits. However, the existing literature knowledge on spatial prevalence is sparse for most appearance traits, including those investigated here. Due to the limitations in appearance trait prevalence knowledge, our results render the use of trait prevalence-informed priors in DNA-based appearance trait prediction currently infeasible.

Exploring the possibility of predicting human head hair greying from DNA using whole-exome and targeted NGS data

Background

Greying of the hair is an obvious sign of human aging. In addition to age, sex- and ancestry-specific patterns of hair greying are also observed and the progression of greying may be affected by environmental factors. However, little is known about the genetic control of this process. This study aimed to assess the potential of genetic data to predict hair greying in a population of nearly 1000 individuals from Poland.

Results

The study involved whole-exome sequencing followed by targeted analysis of 378 exome-wide and literature-based selected SNPs. For the selection of predictors, the minimum redundancy maximum relevance (mRMRe) method was used, and then two prediction models were developed. The models included age, sex and 13 unique SNPs. Two SNPs of the highest mRMRe score included whole-exome identified KIF1A rs59733750 and previously linked with hair loss FGF5 rs7680591. The model for greying vs. no greying prediction achieved accuracy of cross-validated AUC = 0.873. In the 3-grade classification cross-validated AUC equalled 0.864 for no greying, 0.791 for mild greying and 0.875 for severe greying. Although these values present fairly accurate prediction, most of the prediction information was brought by age alone. Genetic variants explained < 10% of hair greying variation and the impact of particular SNPs on prediction accuracy was found to be small.

Conclusions

The rate of changes in human progressive traits shows inter-individual variation, therefore they are perceived as biomarkers of the biological age of the organism. The knowledge on the mechanisms underlying phenotypic aging can be of special interest to the medicine, cosmetics industry and forensics. Our study improves the knowledge on the genetics underlying hair greying processes, presents prototype models for prediction and proves hair greying being genetically a very complex trait. Finally, we propose a four-step approach based on genetic and epigenetic data analysis allowing for i) sex determination; ii) genetic ancestry inference; iii) greying-associated SNPs assignment and iv) epigenetic age estimation, all needed for a final prediction of greying.

Plasma Zinc Levels in Males with Androgenetic Alopecia as Possible Predictors of the Subsequent Conservative Therapy's Effectiveness

Androgenic alopecia (AGA) is the most common type of progressive hair loss in man. The search for reliable predictors of the conservative treatment’s effectiveness is an urgent problem today. Forty-eight patients with AGA, stages I–IV by the Norwood–Hamilton scale, were treated for 4 months with 5% topical minoxidil joints with corrections for trace element and vitamin imbalances. In most cases, the positive therapy’s effect was shown in the parietal but not in the occipital area, whereas that effect was observed in others. The attempts to associate the therapy’s effectiveness with initially defined genetic, hormonal, and metabolic parameters showed the absence of differences between groups with positive and negative outcomes. Among the studied nutrient parameters (Zn, Cu, Mg, Ca, Fe, and Se, as well as vitamins B12, E, D, and folic acid), differences between these groups was shown in zinc content only. The starting point from a zinc plasma level above 10 µmol/L likely provides the success of the subsequent conservative therapy and correlates with an increase in the hair density and diameter in the parietal area. The integral predictive value of the Zn plasma level was assessed as 72.3% (positive predictive value: −88%; and negative predictive value: −55%).

The challenge of predicting human pigmentation traits in degraded bone samples with the MPS-based HIrisPlex-S system

Identification of human remains is an important part of human DNA analysis studies. STR and mitochondrial DNA markers are well suited for the analysis of degraded biological samples including bone material. However, these DNA markers may be useless when reference material is not available. In these cases, predictive DNA analysis can support the process of human identification by providing investigative leads. Forensic DNA phenotyping has progressed significantly by offering new methods based on massively parallel sequencing technology, but the frequent degradation processes observed in skeletal remains can make analysis of such samples challenging. In this study, we demonstrate the usefulness of a recently established Ion AmpliSeq^TM HIrisPlex-S panel using Ion Torrent technology for analyzing bone samples that show different levels of DNA degradation. In total, 63 bone samples at post-mortem intervals up to almost 80 years were genotyped and eye, hair and skin colour predictions were performed using the HIrisPlex-S models. Following the recommended coverage thresholds, it was possible to establish full DNA profiles comprising of 41 DNA variants for 35 samples (55.6%). For 5 samples (7.9%) no DNA profiles were generated. The remaining 23 samples (36.5%) produced partial profiles and showed a clear underperformance of 3 HIrisPlex-S SNPs - rs1545397 (OCA2), rs1470608 (OCA2) and rs10756819 (BNC2), all used for skin colour prediction only. None of the 23 samples gave complete genotypes needed for skin colour prediction was obtained, and in 7 of them (25.9%) the 3 underperformed SNPs were the cause. At the same time, the prediction of eye and hair colour using complete IrisPlex and HIrisPlex profiles could be made for these 23 samples in 20 (87.0%) and 12 cases (52.2%), respectively. Complete HIrisPlex-S profiles were generated from as little as 49 pg of template DNA. Five samples for which the HIrisPlex-S analysis failed, consistently failed in standard STR analysis. Importantly, the 3 underperforming SNPs produced significantly lower number of reads in good quality samples. Nonetheless, the AUC loss resulting from missing data for these 3 SNPs is not considered large (≤0.004) and the prediction of pigmentation from partial profiles is also available in the current HPS tool. The study shows that DNA degradation and the resulting loss of data are the most serious challenge to DNA phenotyping of skeletal remains. Although the newly developed HIrisPlex-S panel has been successfully validated in the current research, primer redesign for the 3 underperforming SNPs in the MPS design should be considered in the future.

A review of the treatment of male pattern hair loss

Introduction: Androgenetic alopecia is a common hair loss disorder affecting up to 80% of males by the age of 80. It is characterized by androgen related progressive thinning of hair in a defined pattern. It results in diminished self-esteem, reduced confidence and distress in affected men, irrespective of age or stage of baldness. An effective treatment for hair baldness is needed.Areas covered: In androgenetic alopecia, hair follicles undergo progressive miniaturization. Genetic factors and androgens are key role-players in disease pathogenesis. Herein the authors review the pharmacologic treatment of androgenetic alopecia, which involves 5 alpha reductase inhibitors, minoxidil and prostaglandins. Non-pharmacologic approaches are also explored.Expert opinion: Androgenetic alopecia progresses over time and although the current available medical treatments like finasteride and minoxidil are effective in arresting the progression of the disease, they allow only partial regrowth of hair at its best. Early treatment achieves a more optimal outcome. Non-pharmacologic treatments like PRP can be considered in patients refractory to medical treatment.Abbreviations: MPHL: male pattern hair loss; AGA: androgenetic alopecia; DHT: dihydrotestosterone; 5AR: 5-alpha-reductase; VEGF: vascular endothelial growth factor; PG's: prostaglandins (PG's); PGD2R: prostaglandin D2 receptor; VPA: valproic aid; SR: Serenoa Repens; PRP: platelet-rich plasma; PDGF: platelet derived growth factor; TGF: transforming growth factor; ERK: extracellular signal-regulated kinase; PKB: protein kinase B; LLLT: low-level laser therapy; ROS: reactive oxygen species; RCT: randomized control trial; SFRP1: secreted frizzled related protein 1; DP: dermal papilla; PDE5: phosphodiesterase 5.

Precision Medicine and the Practice of Trichiatry: Adapting the Concept

Evidence-based medicine (EBM) aims for the ideal that healthcare professionals make conscientious, explicit, and judicious use of the best available evidence gained from the scientific method to clinical decision-making. It seeks to assess the strength of the evidence for benefits of diagnostic tests and treatments, using techniques from science, engineering, and statistics, such as the systematic review of medical literature, meta-analysis, risk-benefit analysis, and randomized controlled trials. The limited success rate of EBM therapies suggests that the complex nature of hair loss may be inadequately served by the present levels of evidence, and that physicians treating hair loss may have fallen short of adequately researching a robust evidence to underpin their practices. Against this backdrop, the concept of precision medicine (PM) is evolving. PM refers to the customization of medical care to the patient's individual characteristics based on the patient's genetic background and other molecular or cellular analysis, while classifying patients into subpopulations that differ in their susceptibility to a particular medical condition, in the biology or prognosis of those medical conditions, or in their response to a specific treatment. With the advances in hair research, the powerful tools of molecular biology and genetics, and innovative technologies, we have the robust scientific data and tools to adapt the concept of PM to the practice of trichiatry. Finally, databases pertaining to the development and efficacy of PM must be analyzed and be used to form the basis of evidence-based personalized trichiatry.

Update on the predictability of tall stature from DNA markers in Europeans

Predicting adult height from DNA has important implications in forensic DNA phenotyping. In 2014, we introduced a prediction model consisting of 180 height-associated SNPs based on data from 10,361 Northwestern Europeans enriched with tall individuals (770 > 1.88 standard deviation), which yielded a mid-ranged accuracy (AUC = 0.75 for binary prediction of tall stature and R² = 0.12 for quantitative prediction of adult height). Here, we provide an update on DNA-based height predictability considering an enlarged list of subsequently-published height-associated SNPs using data from the same set of 10,361 Europeans. A prediction model based on the full set of 689 SNPs showed an improved accuracy relative to previous models for both tall stature (AUC = 0.79) and quantitative height (R² = 0.21). A feature selection analysis revealed a subset of 412 most informative SNPs while the corresponding prediction model retained most of the accuracy (AUC = 0.76 and R² = 0.19) achieved with the full model. Over all, our study empirically exemplifies that the accuracy for predicting human appearance phenotypes with very complex underlying genetic architectures, such as adult height, can be improved by increasing the number of phenotype-associated DNA variants. Our work also demonstrates that a careful sub-selection allows for a considerable reduction of the number of DNA predictors that achieve similar prediction accuracy as provided by the full set. This is forensically relevant due to restrictions in the number of SNPs simultaneously analyzable with forensically suitable DNA technologies in the current days of targeted massively parallel sequencing in forensic genetics.

Towards broadening Forensic DNA Phenotyping beyond pigmentation: Improving the prediction of head hair shape from DNA

Human head hair shape, commonly classified as straight, wavy, curly or frizzy, is an attractive target for Forensic DNA Phenotyping and other applications of human appearance prediction from DNA such as in paleogenetics. The genetic knowledge underlying head hair shape variation was recently improved by the outcome of a series of genome-wide association and replication studies in a total of 26,964 subjects, highlighting 12 loci of which 8 were novel and introducing a prediction model for Europeans based on 14 SNPs. In the present study, we evaluated the capacity of DNA-based head hair shape prediction by investigating an extended set of candidate SNP predictors and by using an independent set of samples for model validation. Prediction model building was carried out in 9674 subjects (6068 from Europe, 2899 from Asia and 707 of admixed European and Asian ancestries), used previously, by considering a novel list of 90 candidate SNPs. For model validation, genotype and phenotype data were newly collected in 2415 independent subjects (2138 Europeans and 277 non-Europeans) by applying two targeted massively parallel sequencing platforms, Ion Torrent PGM and MiSeq, or the MassARRAY platform. A binomial model was developed to predict straight vs. non-straight hair based on 32 SNPs from 26 genetic loci we identified as significantly contributing to the model. This model achieved prediction accuracies, expressed as AUC, of 0.664 in Europeans and 0.789 in non-Europeans; the statistically significant difference was explained mostly by the effect of one EDAR SNP in non-Europeans. Considering sex and age, in addition to the SNPs, slightly and insignificantly increased the prediction accuracies (AUC of 0.680 and 0.800, respectively). Based on the sample size and candidate DNA markers investigated, this study provides the most robust, validated, and accurate statistical prediction models and SNP predictor marker sets currently available for predicting head hair shape from DNA, providing the next step towards broadening Forensic DNA Phenotyping beyond pigmentation traits.

Genetic prediction of male pattern baldness

Male pattern baldness can have substantial psychosocial effects, and it has been phenotypically linked to adverse health outcomes such as prostate cancer and cardiovascular disease. We explored the genetic architecture of the trait using data from over 52,000 male participants of UK Biobank, aged 40-69 years. We identified over 250 independent genetic loci associated with severe hair loss (P<5x10-8). By splitting the cohort into a discovery sample of 40,000 and target sample of 12,000, we developed a prediction algorithm based entirely on common genetic variants that discriminated (AUC = 0.78, sensitivity = 0.74, specificity = 0.69, PPV = 59%, NPV = 82%) those with no hair loss from those with severe hair loss. The results of this study might help identify those at greatest risk of hair loss, and also potential genetic targets for intervention.

The association between HDAC9 gene polymorphisms and stroke risk in the Chinese population: A meta-analysis

Several recent genome-wide association studies (GWASs) have suggested that the histone deacetylase 9 (HDAC9) gene is associated with stroke, but the reliability of these findings remains controversial, particularly for the data derived from different ethnicities and geographical locations. Therefore, we performed a meta-analysis to explore the associations between HDAC9 polymorphisms and the risk of stroke in the Chinese population. All eligible case-control studies that met the search criteria were retrieved from multiple databases, and six case-control studies with a total of 2,356 stroke patients and 3,420 healthy controls were included. The pooled odds ratios (ORs) with 95% confidence intervals (95% CIs) were calculated to assess the strengths of the associations of 3 HDAC9 gene polymorphisms with stroke risk. Our results revealed statistically significant associations of the rs2107595 (T/C) polymorphism with an increased risk of stroke in the allele, codominant and dominant models. Additionally, the rs2389995 (G/A) polymorphism was found to be significantly associated with a decreased risk of stroke in all genetic models. In conclusion, this meta-analysis suggested that the T allele of rs2107595 in HDAC9 increases the risk of stroke but that the G allele of rs2389995 decreases the risk of stroke in the Chinese population.

Development of a methylation marker set for forensic age estimation using analysis of public methylation data and the Agena Bioscience EpiTYPER system

Individual age estimation has the potential to provide key information that could enhance and extend DNA intelligence tools. Following predictive tests for externally visible characteristics developed in recent years, prediction of age could guide police investigations and improve the assessment of age-related phenotype expression patterns such as hair colour changes and early onset of male pattern baldness. DNA methylation at CpG positions has emerged as the most promising DNA tests to ascertain the individual age of the donor of a biological contact trace. Although different methodologies are available to detect DNA methylation, EpiTYPER technology (Agena Bioscience, formerly Sequenom) provides useful characteristics that can be applied as a discovery tool in localized regions of the genome. In our study, a total of twenty-two candidate genomic regions, selected from the assessment of publically available data from the Illumina HumanMethylation 450 BeadChip, had a total of 177 CpG sites with informative methylation patterns that were subsequently investigated in detail. From the methylation analyses made, a novel age prediction model based on a multivariate quantile regression analysis was built using the seven highest age-correlated loci of ELOVL2, ASPA, PDE4C, FHL2, CCDC102B, C1orf132 and chr16:85395429. The detected methylation levels in these loci provide a median absolute age prediction error of ±3.07years and a percentage of prediction error relative to the age of 6.3%. We report the predictive performance of the developed model using cross validation of a carefully age-graded training set of 725 European individuals and a test set of 52 monozygotic twin pairs. The multivariate quantile regression age predictor, using the CpG sites selected in this study, has been placed in the open-access Snipper forensic classification website.

Evaluation of the predictive capacity of DNA variants associated with straight hair in Europeans

DNA-based prediction of hair morphology, defined as straight, curly or wavy hair, could contribute to an improved description of an unknown offender and allow more accurate forensic reconstructions of physical appearance in the field of forensic DNA phenotyping. Differences in scalp hair morphology are significant at the worldwide scale and within Europe. The only genome-wide association study made to date revealed the Trichohyalin gene (TCHH) to be significantly associated with hair morphology in Europeans and reported weaker associations for WNT10A and FRAS1 genes. We conducted a study that centered on six SNPs located in these three genes with a sample of 528 individuals from Poland. The predictive capacity of the candidate DNA variants was evaluated using logistic regression; classification and regression trees; and neural networks, by applying a 10-fold cross validation procedure. Additionally, an independent test set of 142 males from six European populations was used to verify performance of the developed prediction models. Our study confirmed association of rs11803731 (TCHH), rs7349332 (WNT10A) and rs1268789 (FRAS1) SNPs with hair morphology. The combined genotype risk score for straight hair had an odds ratio of 2.7 and these predictors explained ∼ 8.2% of the total variance. The selected three SNPs were found to predict straight hair with a high sensitivity but low specificity when a 10-fold cross validation procedure was applied and the best results were obtained using the neural networks approach (AUC=0.688, sensitivity=91.2%, specificity=23.0%). Application of the neural networks model with 65% probability threshold on an additional test set gave high sensitivity (81.4%) and improved specificity (50.0%) with a total of 78.7% correct calls, but a high non-classification rate (66.9%). The combined TTGGGG SNP genotype for rs11803731, rs7349332, rs1268789 (European frequency=4.5%) of all six straight hair-associated alleles was identified as the best predictor, giving >80% probability of straight hair. Finally, association testing of 44 SNPs previously identified to be associated with male pattern baldness revealed a suggestive association with hair morphology for rs4679955 on 3q25.1. The study results reported provide the starting point for the development of a predictive test for hair morphology in Europeans. More studies are now needed to discover additional determinants of hair morphology to improve the predictive accuracy of this trait in forensic analysis.