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Background: Perceived age (PA) has been associated with mortality, genetic variants linked to ageing and several age-related morbidities. However, estimating PA in large datasets is laborious and costly to generate, limiting its practical applicability., Objectives: To determine if estimating PA using deep learning-based algorithms results in the same associations with morbidities and genetic variants as human-estimated perceived age., Methods: Self-supervised learning (SSL) and deep feature transfer (DFT) deep learning (DL) approaches were trained and tested on human-estimated PAs and their corresponding frontal face images of middle-aged to elderly Dutch participants (n = 2679) from a population-based study in the Netherlands. We compared the DL-estimated PAs with morbidities previously associated with human-estimated PA as well as genetic variants in the gene MC1R; we additionally tested the PA associations with MC1R in a new validation cohort (n = 1158)., Results: The DL approaches predicted PA in this population with a mean absolute error of 2.84 years (DFT) and 2.39 years (SSL). In the training-test dataset, we found the same significant (p < 0.05) associations for DL PA with osteoporosis, ARHL, cognition, COPD and cataracts and MC1R, as with human PA. We also found a similar but less significant association for SSL and DFT PAs (0.69 and 0.71 years per allele, p = 0.008 and 0.011, respectively) with MC1R variants in the validation dataset as that found with human, SSL and DFT PAs in the training-test dataset (0.79, 0.78 and 0.71 years per allele respectively; all p < 0.0001)., Conclusions: Deep learning methods can automatically estimate PA from facial images with enough accuracy to replicate known links between human-estimated perceived age and several age-related morbidities. Furthermore, DL predicted perceived age associated with MC1R gene variants in a validation cohort. Hence, such DL PA techniques may be used instead of human estimations in perceived age studies thereby reducing time and costs., (© 2024 The Author(s). Journal of the European Academy of Dermatology and Venereology published by John Wiley & Sons Ltd on behalf of European Academy of Dermatology and Venereology.)

Although national criminal offender DNA databases (NCODDs) including autosomal short tandem repeats (STRs) have been a successful tool to identify criminals for decades in many countries, yet there are many criminal cases they cannot solve. In cases with mixed male-female samples, particularly sexual assault, expanding NCODDs with Y-chromosomal STR (Y-STR) profiles allows database matching in the absence of autosomal STR profiles. Although Y-STR matches are not individual-specific, this can be largely overcome with rapidly mutating Y-STRs (RM Y-STR) allowing separation of paternally related men. Expanding NCODDs with Y-STR profiles is also beneficial for law enforcement in cases without known suspects via familial searching. Expanding NCODDs with Y-STR profiles may raise concerns about genetic privacy and fundamental human rights. A legal analysis of the European Convention on Human Rights revealed that when primarily for reidentifying convicted sex offenders, it would be in line with the case law of the European Court of Human Rights, while a generalized approach primarily for familial searching and involving all types of offenders may not. This paper aims to stimulate a debate among various stakeholders regarding the benefits and risks of expanding NCODDs with Y-STR profiles that in some countries has already been practically implemented., Competing Interests: The authors declare not to have any conflicts of interest other than that MK and AR are inventors of a filed patent applications: no. EP20158807 and US20240209457A1 (``Novel Y-chromosomal short tandem repeat markers for typing male individuals)., (© The Author(s) 2024. Published by Oxford University Press on behalf of Duke University School of Law, Harvard Law School, Oxford University Press, and Stanford Law School.)

The genetic characterization and identification of individuals who contributed to biological mixtures are complex and mostly unresolved tasks. These tasks are relevant in various fields, particularly in forensic investigations, which frequently encounters crime scene stains generated by more than one person. Currently, forensic mixture deconvolution is mostly performed subsequent to forensic DNA profiling at the level of the mixed DNA profiles, which comes with several limitations. Some previous studies attempted at separating single cells prior to forensic DNA profiling. However, these approaches are biased at selection of the cells and, due to their targeted DNA analysis on low template DNA, provide incomplete and unreliable forensic DNA profiles. We recently demonstrated the feasibility of performing mixture deconvolution prior to forensic DNA profiling through the utilization of a non-targeted single-cell transcriptome sequencing (scRNA-seq). In addition to individual-specific mixture deconvolution, this approach also allowed accurate characterisation of biological sex, biogeographic ancestry and individual identification of the separated mixture contributors. However, RNA has the forensic disadvantage of being prone to degradation, and sequencing RNA - focussing on coding regions - limits the number of single nucleotide polymorphisms (SNPs) utilized for genetic mixture deconvolution, characterization, and identification. These limitations can be overcome by performing single-cell sequencing on the level of DNA instead of RNA. Here, for the first time, we applied non-targeted single-cell DNA sequencing (scDNA-seq) by applying the scATAC-seq (Assay for Transposase-Accessible Chromatin with sequencing) technique to address the challenges of mixture deconvolution in the forensic context. We demonstrated that scATAC-seq, together with our recently developed De-goulash data analysis pipeline, is capable of deconvoluting complex blood mixtures of five individuals from both sexes with varying biogeographic ancestries. We further showed that our approach achieved correct genetic characterization of the biological sex and the biogeographic ancestry of each of the separated mixture contributors and established their identity. Furthermore, by analysing in-silico generated scATAC-seq data mixtures, we demonstrated successful individual-specific mixture deconvolution of i) highly complex mixtures of 11 individuals, ii) balanced mixtures containing as few as 20 cells (10 per each individual), and iii) imbalanced mixtures with a ratio as low as 1:80. Overall, our proof-of-principle study demonstrates the general feasibility of scDNA-seq in general, and scATAC-seq in particular, for mixture deconvolution, genetic characterization and individual identification of the separated mixture contributors. Furthermore, it shows that compared to scRNA-seq, scDNA-seq detects more SNPs from fewer cells, providing higher sensitivity, that is valuable in forensic genetics., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Linear regression (LR) is vastly used in data analysis for continuous outcomes in biomedicine and epidemiology. Despite its popularity, LR is incompatible with missing data, which frequently occur in health sciences. For parameter estimation, this shortcoming is usually resolved by complete-case analysis or imputation. Both work-arounds, however, are inadequate for prediction, since they either fail to predict on incomplete records or ignore missingness-induced reduction in prediction accuracy and rely on (unrealistic) assumptions about the missing mechanism. Here, we derive adaptive predictor-set linear model (aps-lm), capable of making predictions for incomplete data without the need for imputation. It is derived by using a predictor-selection operation, the Moore-Penrose pseudoinverse, and the reduced QR decomposition. aps-lm is an LR generalization that inherently handles missing values. It is applied on a reference data set, where complete predictors and outcome are available, and yields a set of privacy-preserving parameters. In a second stage, these are shared for making predictions of the outcome on external data sets with missing entries for predictors without imputation. Moreover, aps-lm computes prediction errors that account for the pattern of missing values even under extreme missingness. We benchmark aps-lm in a simulation study. aps-lm showed greater prediction accuracy and reduced bias compared to popular imputation strategies under a wide range of scenarios including variation of sample size, goodness of fit, missing value type, and covariance structure. Finally, as a proof-of-principle, we apply aps-lm in the context of epigenetic aging clocks, linear models that predict a person's biological age from epigenetic data with promising clinical applications., (© 2024 The Author(s). Biometrical Journal published by Wiley‐VCH GmbH.)

Aim: To assess the short-term, real-world use and effectiveness of glucagon-like peptide-1 receptor agonist (GLP-1RA) medications in the management of type 2 diabetes (T2D) in a diverse cohort of youth., Methods: This multicentre retrospective study analysed youth prescribed a GLP-1RA for the management of T2D at two academic paediatric diabetes centres prior to June 2022. Change in HbA1c and insulin use from baseline to first (median 91 days) and second (median 190 days) follow-up were evaluated for those taking a GLP-1RA. Multivariable linear mixed effects models adjusting for baseline sex, age, race/ethnicity, insurance, insulin regimen, metformin regimen, GLP-1RA dosing frequency and the body mass index Z-score (BMI-Z) examined the change in HbA1c for participants for up to 6 months after baseline., Results: A total of 136 patients with T2D (median age 16.1 [interquartile range 13.9-18.0] years, 54% female, 56% non-Hispanic Black, 24% Hispanic, 77% with public insurance) were prescribed GLP-1RAs and taking them at first or second follow-up. Median HbA1c decreased from 7.9% to 7.6% (P < .001) at a median follow-up of 91 days (n = 109) and, among those with HbA1c available at baseline and second follow-up (n = 83), from 8.4% to 7.4%. The proportion of patients prescribed insulin decreased from baseline to the first follow-up visit (basal 69% to 60% [P = .008], prandial 46% to 38% [P = .03]). In multivariable analysis, there was a mean decrease in HbA1c by 0.09 percentage points per month (P = .005, 95% confidence interval -0.15, -0.03)., Conclusions: Real-world use of GLP-1RAs in youth with T2D is associated with decreased HbA1c levels, despite challenges with access and adherence. GLP-1RA treatment may reduce insulin doses for youth with T2D., (© 2024 John Wiley & Sons Ltd.)

Introduction: Comprehensive sexuality education (CSE) is associated with positive sexual and reproductive health (SRH) outcomes, including increased contraceptive use, lower rates of unintended pregnancy and prevention of sexual violence. However, implementation of and requirements for CSE vary across the United States which can negatively impact students, both during and beyond high school, including among college students., Methods: and Analysis: This paper describes the research protocol for a multi-staged approach for designing, implementing and evaluating an SRH course for up to 60 undergraduate students at a public university in California. Before the class is offered, we will conduct 20 in-depth interviews with current students, educators and course design experts to learn from their experiences and seek their guidance on course design. To evaluate the course, enrolled students will complete a pre-course and a post-course survey before and after class is taught, to assess students' attitudes and values relevant to educational concepts and the format and delivery of the course and its modules and activities. Approximately 20 students will take part in an in-depth exit interview, after completing the course, to gather perceptions about how the course impacted their knowledge and behavior. The goal is to refine materials for future in-person course offerings and develop a prototype for a fully online version of the course., Discussion: This study introduces a novel university-level course to provide young adult students comprehensive, evidence-based education on sexual and reproductive health from a public health perspective. The program leverages existing CSE efforts, enhancing them with academic rigor, inclusive content and digital inclusion. This approach, inclusive of diverse sexual orientations, content on pleasure and sexual violence prevention, aims to fill existing gaps in university curricula and also set a new standard in CSE. The project's innovative and multidisciplinary design offers a model for broader impact within a large public university system and beyond., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Background: Efficient identification of individuals at high risk of skin cancer is crucial for implementing personalized screening strategies and subsequent care. While Artificial Intelligence holds promising potential for predictive analysis using image data, its application for skin cancer risk prediction utilizing facial images remains unexplored. We present a neural network-based explainable artificial intelligence (XAI) approach for skin cancer risk prediction based on 2D facial images and compare its efficacy to 18 established skin cancer risk factors using data from the Rotterdam Study., Methods: The study employed data from the Rotterdam population-based study in which both skin cancer risk factors and 2D facial images and the occurrence of skin cancer were collected from 2010 to 2018. We conducted a deep-learning survival analysis based on 2D facial images using our developed XAI approach. We subsequently compared these results with survival analysis based on skin cancer risk factors using cox proportional hazard regression., Findings: Among the 2810 participants (mean Age = 68.5 ± 9.3 years, average Follow-up = 5.0 years), 228 participants were diagnosed with skin cancer after photo acquisition. Our XAI approach achieved superior predictive accuracy based on 2D facial images (c-index = 0.72, 95% CI: 0.70-0.74), outperforming that of the known risk factors (c-index = 0.59, 95% CI 0.57-0.61)., Interpretation: This proof-of-concept study underscores the high potential of harnessing facial images and a tailored XAI approach as an easily accessible alternative over known risk factors for identifying individuals at high risk of skin cancer., Funding: The Rotterdam Study is funded through unrestricted research grants from Erasmus Medical Center and Erasmus University, Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. G.V. Roshchupkin is supported by the ZonMw Veni grant (Veni, 549 1936320)., Competing Interests: The authors declare the following financial interests which may be considered potential competing interests: The Erasmus MC Department of Dermatology has received an unrestricted research grant from SkinVision B.V. None of the authors received any direct fees for consulting or salary from the company. T.E. Sangers reports receiving personal consultancy fees from Mylan B.V. and speakers honoraria from Pfizer, Janssen-Cilag, UCB, and Eli Lilly. There are no other declarations of interest., (© 2024 The Author(s).)

Y-chromosomal short tandem repeats (Y-STRs) are widely used in forensic, genealogical, and population genetics. With the recent increase in the number of rapidly mutating (RM) Y-STRs, an unprecedented level of male differentiation can be achieved, widening and improving the applications of Y-STRs in various fields, including forensics. The growing complexity of Y-STR data increases the need for automated data analyses, but dedicated software tools are scarce. To address this, we present the Male Pedigree Toolbox (MPT), a software tool for the automated analysis of Y-STR data in the context of patrilineal genealogical relationships. The MPT can estimate mutation rates and male relative differentiation rates from input Y-STR pedigree data. It can aid in determining ancestral haplotypes within a pedigree and visualize the genetic variation within pedigrees in all branches of family trees. Additionally, it can provide probabilistic classifications using machine learning, helping to establish or prove the structure of the pedigree and the level of relatedness between males, even for closely related individuals with highly similar haplotypes. The tool is flexible and easy to use and can be adjusted to any set of Y-STR markers by modifying the intuitive input file formats. We introduce the MPT software tool v1.0 and make it publicly available with the goal of encouraging and supporting forensic, genealogical, and other geneticists in utilizing the full potential of Y-STRs for both research purposes and practical applications, including criminal casework.

Motivation: We introduce SMapper, a novel web and software tool for visualizing spatial prevalence data of all types including those suffering from incomplete geographic coverage and insufficient sample sizes. We demonstrate the benefits of our tool in overcoming interpretational issues with existing tools caused by such data limitations. We exemplify the use of SMapper by applications to human genotype and phenotype data relevant in an epidemiological, anthropological and forensic context., Availability and Implementation: A web implementation is available at https://rhodos.ccg.uni-koeln.de/smapper/. A stand-alone version, released under the GNU General Public License version 3 as published by the Free Software Foundation, is available from https://rhodos.ccg.uni-koeln.de/smapper/software-download.php as a Singularity container (https://docs.sylabs.io/guides/latest/user-guide/index.html) and a native Linux Python installation., Competing Interests: None declared., (© The Author(s) 2023. Published by Oxford University Press.)

Human ear morphology, a complex anatomical structure represented by a multidimensional set of correlated and heritable phenotypes, has a poorly understood genetic architecture. In this study, we quantitatively assessed 136 ear morphology traits using deep learning analysis of digital face images in 14,921 individuals from five different cohorts in Europe, Asia, and Latin America. Through GWAS meta-analysis and C-GWASs, a recently introduced method to effectively combine GWASs of many traits, we identified 16 genetic loci involved in various ear phenotypes, eight of which have not been previously associated with human ear features. Our findings suggest that ear morphology shares genetic determinants with other surface ectoderm-derived traits such as facial variation, mono eyebrow, and male pattern baldness. Our results enhance the genetic understanding of human ear morphology and shed light on the shared genetic contributors of different surface ectoderm-derived phenotypes. Additionally, gene editing experiments in mice have demonstrated that knocking out the newly ear-associated gene (Intu) and a previously ear-associated gene (Tbx15) causes deviating mouse ear morphology., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Cancer continues to be the leading cause of mortality in high-income countries, necessitating the development of more precise and effective treatment modalities. Immunotherapy, specifically adoptive cell transfer of T cell receptor (TCR)-engineered T cells (TCR-T therapy), has shown promise in engaging the immune system for cancer treatment. One of the biggest challenges in the development of TCR-T therapies is the proper prediction of the pairing between TCRs and peptide-human leukocyte antigen (pHLAs). Modern computational immunology, using artificial intelligence (AI)-based platforms, provides the means to optimize the speed and accuracy of TCR screening and discovery., Objective: This study proposes an observational clinical trial protocol to collect patient samples and generate a database of pHLA:TCR sequences to aid the development of an AI-based platform for efficient selection of specific TCRs., Methods: The multicenter observational study, involving 8 participating hospitals, aims to enroll patients diagnosed with stage II, III, or IV colorectal cancer adenocarcinoma., Results: Patient recruitment has recently been completed, with 100 participants enrolled. Primary tumor tissue and peripheral blood samples have been obtained, and peripheral blood mononuclear cells have been isolated and cryopreserved. Nucleic acid extraction (DNA and RNA) has been performed in 86 cases. Additionally, 57 samples underwent whole exome sequencing to determine the presence of somatic mutations and RNA sequencing for gene expression profiling., Conclusions: The results of this study may have a significant impact on the treatment of patients with colorectal cancer. The comprehensive database of pHLA:TCR sequences generated through this observational clinical trial will facilitate the development of the AI-based platform for TCR selection. The results obtained thus far demonstrate successful patient recruitment and sample collection, laying the foundation for further analysis and the development of an innovative tool to expedite and enhance TCR selection for precision cancer treatments., Trial Registration: ClinicalTrials.gov NCT04994093; https://clinicaltrials.gov/ct2/show/NCT04994093., International Registered Report Identifier (irrid): DERR1-10.2196/45872., (©Joanna Bujak, Stanisław Kłęk, Martyna Balawejder, Aleksandra Kociniak, Kinga Wilkus, Rafał Szatanek, Zofia Orzeszko, Joanna Welanyk, Grzegorz Torbicz, Mateusz Jęckowski, Tomasz Kucharczyk, Łukasz Wohadlo, Maciej Borys, Honorata Stadnik, Michał Wysocki, Magdalena Kayser, Marta Ewa Słomka, Anna Kosmowska, Karolina Horbacka, Tomasz Gach, Beata Markowska, Tomasz Kowalczyk, Jacek Karoń, Marek Karczewski, Mirosław Szura, Anna Sanecka-Duin, Agnieszka Blum. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 13.07.2023.)

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., Competing Interests: Declaration of Competing Interest All authors were part of the EU Horizon2020-funded VISAGE Consortium and Project (http://www.visage-h2020.eu) that worked on improving, integrating, implementing, disseminating, and socially and ethically assessing Forensic DNA Phenotyping on appearance, bio-geographic ancestry and age. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. MK is a co-inventor of the patent EP2195448A1 “Method to predict iris color” but has not received license fees or royalties from this., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Competing Interests: Declaration of Competing Interest The authors declare no conflict of interest.

Tobacco smoking is a frequent habit sustained by > 1.3 billion people in 2020 and the leading preventable factor for health risk and premature mortality worldwide. In the forensic context, predicting smoking habits from biological samples may allow broadening DNA phenotyping. In this study, we aimed to implement previously published smoking habit classification models based on blood DNA methylation at 13 CpGs. First, we developed a matching lab tool based on bisulfite conversion and multiplex PCR followed by amplification-free library preparation and targeted paired-end massively parallel sequencing (MPS). Analysis of six technical duplicates revealed high reproducibility of methylation measurements (Pearson correlation of 0.983). Artificially methylated standards uncovered marker-specific amplification bias, which we corrected via bi-exponential models. We then applied our MPS tool to 232 blood samples from Europeans of a wide age range, of which 90 were current, 71 former and 71 never smokers. On average, we obtained 189,000 reads/sample and 15,000 reads/CpG, without marker drop-out. Methylation distributions per smoking category roughly corresponded to previous microarray analysis, showcasing large inter-individual variation but with technology-driven bias. Methylation at 11 out of 13 smoking-CpGs correlated with daily cigarettes in current smokers, while solely one was weakly correlated with time since cessation in former smokers. Interestingly, eight smoking-CpGs correlated with age, and one displayed weak but significant sex-associated methylation differences. Using bias-uncorrected MPS data, smoking habits were relatively accurately predicted using both two- (current/non-current) and three- (never/former/current) category model, but bias correction resulted in worse prediction performance for both models. Finally, to account for technology-driven variation, we built new, joint models with inter-technology corrections, which resulted in improved prediction results for both models, with or without PCR bias correction (e.g. MPS cross-validation F 1 -score > 0.8; 2-categories). Overall, our novel assay takes us one step closer towards the forensic application of viable smoking habit prediction from blood traces. However, future research is needed towards forensically validating the assay, especially in terms of sensitivity. We also need to further shed light on the employed biomarkers, particularly on the mechanistics, tissue specificity and putative confounders of smoking epigenetic signatures., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: We were able to demonstrate the feasibility of a new robotic system (Versius, CMR Surgical, Cambridge, UK) for procedures in small inanimate cavities. The aim of this consecutive study was to test the Versius ® system for its feasibility, performance, and safety of robotic abdominal and thoracic surgery in piglets simulating infants with a body weight lower than 10 kg., Methods: A total of 24 procedures (from explorative laparoscopy to thoracoscopic esophageal repair) were performed in 4 piglets with a mean age of 12 days and a mean body weight of 6.4 (7-7.5) kg. Additional urological procedures were performed after euthanasia of the piglet. The Versius ® robotic system was used with 5 mm wristed instruments and a 10 mm 3D 0° or 30° camera. The setup consisted of the master console and three to four separate arms. The performance of the procedure, the size, position, and the distance between the ports, the external and internal collisions, and complications of the procedures were recorded and analyzed., Results: We were able to perform all surgical procedures as planned. We encountered neither surgical nor robot-associated complications in the live model. Whereas all abdominal procedures could be performed successfully under general anesthesia, one piglet was euthanized early before the thoracic interventions, likely due to pulmonary inflammatory response. Technical limitations were based on the size of the camera (10 mm) being too large and the minimal insertion depth of the instruments for calibration of the fulcrum point., Conclusions: Robotic surgery on newborns and infants appears technically feasible with the Versius ® system. Software adjustments for fulcrum point calibration need to be implemented by the manufacturer as a result of our study. To further evaluate the Versius ® system, prospective trials are needed, comparing it to open and laparoscopic surgery as well as to other robotic systems.

Circadian rhythms influence physiology, metabolism, and molecular processes in the human body. Estimation of individual body time (circadian phase) is therefore highly relevant for individual optimization of behavior (sleep, meals, sports), diagnostic sampling, medical treatment, and for treatment of circadian rhythm disorders. Here, we provide a partial least squares regression (PLSR) machine learning approach that uses plasma-derived metabolomics data in one or more samples to estimate dim light melatonin onset (DLMO) as a proxy for circadian phase of the human body. For this purpose, our protocol was aimed to stay close to real-life conditions. We found that a metabolomics approach optimized for either women or men under entrained conditions performed equally well or better than existing approaches using more labor-intensive RNA sequencing-based methods. Although estimation of circadian body time using blood-targeted metabolomics requires further validation in shift work and other real-world conditions, it currently may offer a robust, feasible technique with relatively high accuracy to aid personalized optimization of behavior and clinical treatment after appropriate validation in patient populations.

Introduction: Exercise limitation is frequently described among asthmatic patients and could be related to different mechanisms of the pulmonary, cardiovascular and muscular systems. Despite this, cardiopulmonary exercise testing (CPET) does not have an established role in the management of severe asthma. The aim of our study was to investigate the role of CPET and inspiratory pressure measurement in exercise capacity and muscle strength in severe asthmatic patients treated with anti-IL-5 therapy., Methods: A monocentric observational study was conducted at Hanover Medical School, Germany, from April 2018 to June 2019. Patients affected by severe asthma treated with either mepolizumab or benralizumab were included. All patients underwent CPET before the initiation of antibody therapy and after 3 months, and follow-up visits were scheduled at 3, 6 and 12 months with plethysmography, inspiratory pressure measurement and blood gas analysis., Results: 14 patients were enrolled: 10 (71.4%) females, median age 52 years (IQR 47-61). Seven patients were treated with benralizumab, seven with mepolizumab. Oxygen uptake ( V ' O 2 peak) did not change significantly after 3 months of antibody treatment, while the mean value of the breathing reserve exhaustion reduced significantly from 78% to 60% (p=0.004). Whereas at baseline seven patients depleted the breathing reserve and two of them experienced oxygen desaturation during exercise, at 3 months no one presented any desaturation or breathing reserve exhaustion. The inspiratory pressure remained unchanged before and after the antibody therapy., Conclusion: CPET could show hints of alveolar recruitment and ventilatory efficiency in severe asthma patients treated with antibody therapy., Competing Interests: Conflict of interest: None declared., (Copyright ©The authors 2023.)

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., (© 2022. The Author(s).)

Background: Looking older for one's chronological age is associated with a higher mortality rate. Yet it remains unclear how perceived facial age relates to morbidity and the degree to which facial ageing reflects systemic ageing of the human body., Objectives: To investigate the association between ΔPA and age-related morbidities of different organ systems, where ΔPA represents the difference between perceived age (PA) and chronological age., Methods: We performed a cross-sectional analysis on data from the Rotterdam Study, a population-based cohort study in the Netherlands. High-resolution facial photographs of 2679 men and women aged 51.5-87.8 years of European descent were used to assess PA. PA was estimated and scored in 5-year categories using these photographs by a panel of men and women who were blinded for chronological age and medical history. A linear mixed model was used to generate the mean PAs. The difference between the mean PA and chronological age was calculated (ΔPA), where a higher (positive) ΔPA means that the person looks younger for their age and a lower (negative) ΔPA that the person looks older. ΔPA was tested as a continuous variable for association with ageing-related morbidities including cardiovascular, pulmonary, ophthalmological, neurocognitive, renal, skeletal and auditory morbidities in separate regression analyses, adjusted for age and sex (model 1) and additionally for body mass index, smoking and sun exposure (model 2)., Results: We observed 5-year higher ΔPA (i.e. looking younger by 5 years for one's age) to be associated with less osteoporosis [odds ratio (OR) 0.76, 95% confidence interval (CI) 0.62-0.93], less chronic obstructive pulmonary disease (OR 0.85, 95% CI 0.77-0.95), less age-related hearing loss (model 2; B = -0.76, 95% CI -1.35 to -0.17) and fewer cataracts (OR 0.84, 95% CI 0.73-0.97), but with better global cognitive functioning (g-factor; model 2; B = 0.07, 95% CI 0.04-0.10)., Conclusions: PA is associated with multiple morbidities and better cognitive function, suggesting that systemic ageing and cognitive ageing are, to an extent, externally visible in the human face., Competing Interests: Conflicts of interest D.A.G. is a Unilever employee and as an author had an influence on the analyses and interpretation of the results. Although no products were tested, these results could be used more generally to promote antiageing products and services that lead to financial gain for Unilever., (© The Author(s) 2023. Published by Oxford University Press on behalf of British Association of Dermatologists. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Identifying individuals from biological mixtures to which they contributed is highly relevant in crime scene investigation and various biomedical research fields, but despite previous attempts, remains nearly impossible. Here we investigated the potential of using single-cell transcriptome sequencing (scRNA-seq), coupled with a dedicated bioinformatics pipeline (De-goulash), to solve this long-standing problem. We developed a novel approach and tested it with scRNA-seq data that we de-novo generated from multi-person blood mixtures, and also in-silico mixtures we assembled from public single individual scRNA-seq datasets, involving different numbers, ratios, and bio-geographic ancestries of contributors. For all 2 up to 9-person balanced and imbalanced blood mixtures with ratios up to 1:60, we achieved a clear single-cell separation according to the contributing individuals. For all separated mixture contributors, sex and bio-geographic ancestry (maternal, paternal, and bi-parental) were correctly determined. All separated contributors were correctly individually identified with court-acceptable statistical certainty using de-novo generated whole exome sequencing reference data. In this proof-of-concept study, we demonstrate the feasibility of single-cell approaches to deconvolute biological mixtures and subsequently genetically characterise, and individually identify the separated mixture contributors. With further optimisation and implementation, this approach may eventually allow moving to challenging biological mixtures, including those found at crime scenes., (© 2023. The Author(s).)

Rapidly mutating Y-chromosomal short tandem repeats (RM Y-STRs) were suggested for differentiating patrilineally related men as relevant in forensic genetics, anthropological genetics, and genetic genealogy. Empirical data are available for closely related males, while differentiation rates for more distant relatives are scarce. Available RM Y-STR mutation rate estimates are typically based on father-son pair data, while pedigree-based studies for efficient analysis requiring less samples are rare. Here, we present a large-scale pedigree analysis in 9379 pairs of men separated by 1-34 meioses on 30 Y-STRs with increased mutation rates including all known RM Y-STRs (RMplex). For comparison, part of the samples were genotyped at 25 standard Y-STRs mostly with moderate mutation rates (Yfiler Plus). For 43 of the 49 Y-STRs analyzed, pedigree-based mutation rates were similar to previous father-son based estimates, while for six markers significant differences were observed. Male relative differentiation rates from the 30 RMplex Y-STRs were 43%, 84%, 96%, 99%, and 100% for relatives separated by one, four, six, nine, and twelve meioses, respectively, which largely exceeded rates obtained by 25 standard Y-STRs. Machine learning based models for predicting the degree of patrilineal consanguinity yielded accurate and reasonably precise predictions when using RM Y-STRs. Fully matching haplotypes resulted in a 95% confidence interval of 1-6 meioses with RMplex compared to 1-25 with Yfiler Plus. Our comprehensive pedigree study demonstrates the value of RM Y-STRs for differentiating male relatives of various types, in many cases achieving individual identification, thereby overcoming the largest limitation of forensic Y-chromosome analysis., (© 2022. The Author(s).)

Standard genome-wide association studies (GWASs) rely on analyzing a single trait at a time. However, many human phenotypes are complex and composed by multiple correlated traits. Here we introduce C-GWAS, a method for combining GWAS summary statistics of multiple potentially correlated traits. Extensive computer simulations demonstrated increased statistical power of C-GWAS compared to the minimal p-values of multiple single-trait GWASs (MinGWAS) and the current state-of-the-art method for combining single-trait GWASs (MTAG). Applying C-GWAS to a meta-analysis dataset of 78 single trait facial GWASs from 10,115 Europeans identified 56 study-wide suggestively significant loci with multi-trait effects on facial morphology of which 17 are novel loci. Using data from additional 13,622 European and Asian samples, 46 (82%) loci, including 9 (53%) novel loci, were replicated at nominal significance with consistent allele effects. Functional analyses further strengthen the reliability of our C-GWAS findings. Our study introduces the C-GWAS method and makes it available as computationally efficient open-source R package for widespread future use. Our work also provides insights into the genetic architecture of human facial appearance., (© 2022. The Author(s).)

Rapidly mutating Y chromosomal short tandem repeat markers (RM Y-STRs) -characterized by at least one mutation per 100 generations- are suitable for differentiating both related and unrelated males. The recently introduced multiplex method RMplex allows for the efficient analysis of 30 Y-STRs with increased mutation rates, including all 26 currently known RM Y-STRs. While currently available RM Y-STR mutation rates were established mostly from European individuals, here we applied RMplex to DNA samples of 178 genetically confirmed father-son pairs from East Asia. For several Y-STRs, we found significantly higher mutation rates in Japanese compared to previous estimates. The consequent father-son differentiation rate based on RMplex was significantly higher (52%) in Japanese than previously reported for Europeans (42%), and much higher than with Yfiler Plus in both sample sets (14% and 13%, respectively). Further analysis suggests that the higher mutation and relative differentiation rates in Japanese can in part be explained by on average longer Y-STR alleles relative to Europeans. Moreover, we show that the most striking difference, which was found in DYS712, could be linked to a Y-SNP haplogroup (O1b2-P49) that is common in Japanese and rare in other populations. We encourage the forensic Y-STR community to generate more RMplex data from more population samples of sufficiently large sample size in combination with Y-SNP data to further investigate population effects on mutation and relative differentiation rates. Until more RMplex data from more populations become available, caution shall be placed when applying RM Y-STR mutation rate estimates established in one population, such as Europeans, to forensic casework involving male suspects of paternal origin from other populations, such as non-Europeans., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

The Massim, a cultural region that includes the southeastern tip of mainland Papua New Guinea (PNG) and nearby PNG offshore islands, is renowned for a trading network called Kula, in which different valuable items circulate in different directions among some of the islands. Although the Massim has been a focus of anthropological investigation since the pioneering work of Malinowski in 1922, the genetic background of its inhabitants remains relatively unexplored. To characterize the Massim genomically, we generated genome-wide SNP data from 192 individuals from 15 groups spanning the entire region. Analyzing these together with comparative data, we found that all Massim individuals have variable Papuan-related (indigenous) and Austronesian-related (arriving ∼3,000 years ago) ancestries. Individuals from Rossel Island in southern Massim, speaking an isolate Papuan language, have the highest amount of a distinct Papuan ancestry. We also investigated the recent contact via sharing of identical by descent (IBD) genomic segments and found that Austronesian-related IBD tracts are widely distributed geographically, but Papuan-related tracts are shared exclusively between the PNG mainland and Massim, and between the Bismarck and Solomon Archipelagoes. Moreover, the Kula-practicing groups of the Massim show higher IBD sharing among themselves than do groups that do not participate in Kula. This higher sharing predates the formation of Kula, suggesting that extensive contact between these groups since the Austronesian settlement may have facilitated the formation of Kula. Our study provides the first comprehensive genome-wide assessment of Massim inhabitants and new insights into the fascinating Kula system., (© The Author(s) 2022. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.)

Human microbiome research is moving from characterization and association studies to translational applications in medical research, clinical diagnostics, and others. One of these applications is the prediction of human traits, where machine learning (ML) methods are often employed, but face practical challenges. Class imbalance in available microbiome data is one of the major problems, which, if unaccounted for, leads to spurious prediction accuracies and limits the classifier's generalization. Here, we investigated the predictability of smoking habits from class-imbalanced saliva microbiome data by combining data augmentation techniques to account for class imbalance with ML methods for prediction. We collected publicly available saliva 16S rRNA gene sequencing data and smoking habit metadata demonstrating a serious class imbalance problem, i.e., 175 current vs. 1,070 non-current smokers. Three data augmentation techniques (synthetic minority over-sampling technique, adaptive synthetic, and tree-based associative data augmentation) were applied together with seven ML methods: logistic regression, k-nearest neighbors, support vector machine with linear and radial kernels, decision trees, random forest, and extreme gradient boosting. K-fold nested cross-validation was used with the different augmented data types and baseline non-augmented data to validate the prediction outcome. Combining data augmentation with ML generally outperformed baseline methods in our dataset. The final prediction model combined tree-based associative data augmentation and support vector machine with linear kernel, and achieved a classification performance expressed as Matthews correlation coefficient of 0.36 and AUC of 0.81. Our method successfully addresses the problem of class imbalance in microbiome data for reliable prediction of smoking habits., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Díez López, Montiel González, Vidaki and Kayser.)

The interocular distance, or orbital telorism, is a distinctive craniofacial trait that also serves as a clinically informative measure. While its extremes, hypo- and hypertelorism, have been linked to monogenic disorders and are often syndromic, little is known about the genetic determinants of interocular distance within the general population. We derived orbital telorism measures from cranial magnetic resonance imaging by calculating the distance between the eyeballs' centre of gravity, which showed a good reproducibility with an intraclass correlation coefficient of 0.991 (95% confidence interval 0.985-0.994). Heritability estimates were 76% (standard error = 12%) with a family-based method (N = 364) and 39% (standard error = 2.4%) with a single nucleotide polymorphism-based method (N = 34 130) and were unaffected by adjustment for height (model II) and intracranial volume (model III) or head width (model IV). Genome-wide association studies in 34 130 European individuals identified 56 significantly associated genomic loci (P < 5 × 10-8) across four different models of which 46 were novel for facial morphology, and overall these findings replicated in an independent sample (N = 10 115) with telorism-related horizontal facial distance measures. Genes located nearby these 56 identified genetic loci were 4.9-fold enriched for Mendelian hypotelorism and hypertelorism genes, underlining their biological relevance. This study provides novel insights into the genetic architecture underlying interocular distance in particular, and the face in general, and explores its potential for applications in a clinical setting., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

The discovery of rapidly mutating (RM) Y-STRs started to move the field of forensic Y-STR analysis from male lineage identification towards male individual identification. Previously, the forensic value of RM Y-STRs for differentiating male relatives was limited due to the modest number of 13 identified RM Y-STRs. Recently, new RM Y-STRs were discovered, with strong expectations for significantly improving male relative differentiation; however, empirical evidence is missing yet. More recently, the genotyping method RMplex for efficiently analyzing 30 Y-STRs with high mutation rates, including all 26 currently known RM Y-STRs, was introduced. Here, we applied RMplex as well as the current state-of-the-art commercial Y-STR kit: Yfiler™ Plus PCR Amplification kit, to several hundreds of DNA-confirmed father-son pairs. Newly established estimates confirmed the high mutation rates of novel and previous RM Y-STRs. By combining current with previous data, we provide updated consensus estimates of mutation rates for all 49 Y-STRs targeted with both methods. Based on RMplex, 42% of 499 father-son pairs were differentiated, while 14% of 530 pairs based on Yfiler™ Plus, and 48% of 499 pairs based on both methods combined. Regarding brothers, RMplex also clearly outperformed Yfiler™ Plus, with differentiation rates of 62% and 33%, respectively. By combining both methods 72.9% of the brothers showed at least one mutation. For unrelated males, both methods achieved a discrimination capacity of 99.8% and a haplotype diversity of 0.999991, since all males had different haplotypes, except for two, perhaps indicating a hidden paternal relationship. Overall, this study underlines the value of RM Y-STRs in general and RMplex in particular for differentiating male relatives highly relevant in forensic genetics. It provides the first empirical evidence on the high value of RMplex for differentiating close male relatives, which for father-son pairs was almost 60% higher than with the initial set of 13 RM Y-STRs and three times higher than with Yfiler™ Plus. Based on our results from closely related males, we expect RMplex to also improve the differentiation of more distantly related males significantly, which needs empirical demonstration in future studies. We encourage the forensic community to apply RMplex in all forensic cases where a match with a commercial Y-STR kit was obtained between the male suspect and the evidence material, or to solely use RMplex in such cases, aiming to find out if the male suspect or any of his male paternal relatives left the evidence material at the crime scene., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: The Versius ® is a recently approved robotic surgical system for general surgery procedures in adults. Before any application in children, data of its feasibility and safety in small cavities has to be compiled, beginning with inanimate models. Therefore, the aim of this preclinical study was to assess the Versius ® system for its performance in small boxes simulating small body cavities., Methods: In total, 8 cardboard boxes of decreasing volumes (15.75 L to 106 mL) were used. The procedures, two single stitches with two square knots each, were performed in every box, starting in the largest and consecutively exchanging the box to the next smaller one. The evaluation included procedure time, port placement and pivot point setup, arrangement of the robotic arms and instrumentation, amount of internal and external instrument-instrument collisions and instrument-box collisions., Results: All procedures could be successfully performed in all boxes. The procedure time decreased due to the learning curve in the first four boxes (15.75 to 1.87 L) and consecutively increased from boxes of 1.22 L up to the smallest box with the dimensions of 4.4 × 4.9 × 4.9 cm 3 . This may be based on the progress of complexity of the procedures in small cavities, which is also depicted by the synchronous increase of the internal instrument-instrument and instrument-box collisions., Conclusion: With the use of the Versius ® robotic surgical system, we were able to perform robotic reconstructive procedures, such as intracorporal suturing and knot tying, in cavities as small as 106 mL. Whether this system is comparable or even superior to conventional laparoscopic surgery in small cavities, such as in children, has to be evaluated. Furthermore, before any application in newborns or infants, ongoing evaluation of this system should be performed in a live animal model.