High-throughput phenotyping methods for quantifying hair fiber morphology

Quantifying the continuous variation in human scalp hair morphology is of interest to anthropologists, geneticists, dermatologists and forensic scientists, but existing methods for studying hair form are time-consuming and not widely used. Here, we present a high-throughput sample preparation protocol for the imaging of both longitudinal (curvature) and cross-sectional scalp hair morphology. Additionally, we describe and validate a new Python package designed to process longitudinal and cross-sectional hair images, segment them, and provide measurements of interest. Lastly, we apply our methods to an admixed African-European sample (n = 140), demonstrating the benefit of quantifying hair morphology over classification, and providing evidence that the relationship between cross-sectional morphology and curvature may be an artefact of population stratification rather than a causal link.

A Centrifuge-Based Method for Identifying Novel Genetic Traits That Affect Root-Substrate Adhesion in Arabidopsis thaliana

The physical presence of roots and the compounds they release affect the cohesion between roots and their environment. However, the plant traits that are important for these interactions are unknown and most methods that quantify the contributions of these traits are time-intensive and require specialist equipment and complex substrates. Our lab developed an inexpensive, high-throughput phenotyping assay that quantifies root-substrate adhesion in Arabidopsis thaliana. We now report that this method has high sensitivity and versatility for identifying different types of traits affecting root-substrate adhesion including root hair morphology, vesicle trafficking pathways, and root exudate composition. We describe a practical protocol for conducting this assay and introduce its use in a forward genetic screen to identify novel genes affecting root-substrate interactions. This assay is a powerful tool for identifying and quantifying genetic contributions to cohesion between roots and their environment.

Protein-coding repeat polymorphisms strongly shape diverse human phenotypes

Hundreds of the proteins encoded in human genomes contain domains that vary in size or copy number due to variable numbers of tandem repeats (VNTRs) in protein-coding exons. VNTRs have eluded analysis by the molecular methods-SNP arrays and high-throughput sequencing-used in large-scale human genetic studies to date; thus, the relationships of VNTRs to most human phenotypes are unknown. We developed ways to estimate VNTR lengths from whole-exome sequencing data, identify the SNP haplotypes on which VNTR alleles reside, and use imputation to project these haplotypes into abundant SNP data. We analyzed 118 protein-altering VNTRs in 415,280 UK Biobank participants for association with 791 phenotypes. Analysis revealed some of the strongest associations of common variants with human phenotypes including height, hair morphology, and biomarkers of human health; for example, a VNTR encoding 13-44 copies of a 19-amino-acid repeat in the chondroitin sulfate domain of aggrecan (ACAN) associated with height variation of 3.4 centimeters (s.e. 0.3 cm). Incorporating large-effect VNTRs into analysis also made it possible to map many additional effects at the same loci: for the blood biomarker lipoprotein(a), for example, analysis of the kringle IV-2 VNTR within the LPA gene revealed that 18 coding SNPs and the VNTR in LPA explained 90% of lipoprotein(a) heritability in Europeans, enabling insights about population differences and epidemiological significance of this clinical biomarker. These results point to strong, cryptic effects of highly polymorphic common structural variants that have largely eluded molecular analyses to date.

High-throughput phenotyping methods for quantifying hair fiber morphology

Quantifying the continuous variation in human scalp hair morphology is of interest to anthropologists, geneticists, dermatologists and forensic scientists, but existing methods for studying hair form are time-consuming and not widely used. Here, we present a high-throughput sample preparation protocol for the imaging of both longitudinal (curvature) and cross-sectional scalp hair morphology. Additionally, we describe and validate a new Python package designed to process longitudinal and cross-sectional hair images, segment them, and provide measurements of interest. Lastly, we apply our methods to an admixed African-European sample (n=140), demonstrating the benefit of quantifying hair morphology over qualitative classification or racial categories, and providing evidence against the long-held belief that cross-sectional morphology predicts curvature.

Comparison of Genome-Wide Association Scans for Quantitative and Observational Measures of Human Hair Curvature

Previous genetic studies on hair morphology focused on the overall morphology of the hair using data collected by self-report or researcher observation. Here, we present the first genome-wide association study (GWAS) of a micro-level quantitative measure of hair curvature. We compare these results to GWAS results obtained using a macro-level classification of observable hair curvature performed in the same sample of twins and siblings of European descent. Observational data were collected by trained observers, while quantitative data were acquired using an Optical Fibre Diameter Analyser (OFDA). The GWAS for both the observational and quantitative measures of hair curvature resulted in genome-wide significant signals at chromosome 1q21.3 close to the trichohyalin (TCHH) gene, previously shown to harbor variants associated with straight hair morphology in Europeans. All genetic variants reaching genome-wide significance for both GWAS (quantitative measure lead single-nucleotide polymorphism [SNP] rs12130862, p = 9.5 × 10–09; observational measure lead SNP rs11803731, p = 2.1 × 10–17) were in moderate to very high linkage disequilibrium (LD) with each other (minimum r2 = .45), indicating they represent the same genetic locus. Conditional analyses confirmed the presence of only one signal associated with each measure at this locus. Results from the quantitative measures reconfirmed the accuracy of observational measures.

Comparative Evaluation of the Clinical Efficacy of PRP-Therapy, Minoxidil, and Their Combination with Immunohistochemical Study of the Dynamics of Cell Proliferation in the Treatment of Men with Androgenetic Alopecia

Platelet-rich plasma (PRP) therapy has been considered as a promising treatment for androgenetic alopecia (AGA). The aim of the study was comparative evaluation of the clinical efficacy of PRP-therapy, minoxidil, and their combination in the treatment of men with AGA and to evaluate the effects of PRP on the proliferation of hair follicle (HF) cells in skin biopsy. Materials and Methods: The study involved 69 men who were divided into 3 groups who received PRP therapy, minoxidil, and their combination. The clinical efficacy of the therapy was evaluated by the dynamics of morphometric of hairs. To assess cell proliferation antibodies to β-catenin, CD34, Ki67, and to Dkk-1 were used. Results. PRP treatment was more effective than minoxidil therapy (p = 0.005). Complex therapy turned out to be more effective than minoxidil monotherapy (p < 0.0001) and PRP monotherapy (p = 0.007). After applying PRP the absolute and relative values of the β-catenin and CD34 expression area increased; an increase in Ki67+ index was also significant. Conclusions: PRP can be considered as a treatment option for AGA. Combined PRP and minoxidil use seems promising for the treatment of AGA. PRP increase in the proliferative activity of HF cells and improves hair morphology in patients with AGA.