The Current Role of Arthroscopy in Traumatic Wrist Injuries: An Expert Survey.

Background Wrist arthroscopy has become increasingly popular for diagnosing and treating traumatic wrist injuries. How wrist arthroscopy has influenced the daily practice of wrist surgeons remains unclear. The objective of this study was to evaluate the role of wrist arthroscopy for the diagnosis and treatment of traumatic wrist injuries among members of the International Wrist Arthroscopy Society (IWAS). Methods An online survey was conducted among IWAS members between August and November 2021 with questions regarding the diagnostic and therapeutic importance of wrist arthroscopy. Questions focused on traumatic injuries of the triangular fibrocartilage complex (TFCC) and scapholunate ligament (SLL). Multiple-choice questions were presented in the form of a Likert scale. The primary outcome was respondent agreement, defined as 80% answering similarly. Results The survey was completed by 211 respondents (39% response rate). The majority (81%) were certified or fellowship-trained wrist surgeons. Most respondents (74%) had performed over 100 wrist arthroscopies. Agreement was reached on 4 of the 22 questions. It was agreed that the outcomes of wrist arthroscopy strongly depend on surgeons' experience, that there is sufficient evidence for the diagnostic purposes of wrist arthroscopy, and that wrist arthroscopy is better than magnetic resonance imaging (MRI) for diagnosing TFCC and SLL injuries. No agreement was reached on the preferred treatment of any type of TFCC or SLL injury. Conclusion There is agreement that wrist arthroscopy is superior to MRI for diagnosing traumatic TFCC and SLL injuries, yet experts remain divided on the optimal management. Guidelines need to be developed for the standardization of indications and procedures. Level of Evidence This is a Level III study.

Implicating causal brain imaging endophenotypes in Alzheimer's disease using multivariable IWAS and GWAS summary data.

Recent evidence suggests the existence of many undiscovered heritable brain phenotypes involved in Alzheimer's Disease (AD) pathogenesis. This finding necessitates methods for the discovery of causal brain changes in AD that integrate Magnetic Resonance Imaging measures and genotypic data. However, existing approaches for causal inference in this setting, such as the univariate Imaging Wide Association Study (UV-IWAS), suffer from inconsistent effect estimation and inflated Type I errors in the presence of genetic pleiotropy, the phenomenon in which a variant affects multiple causal intermediate risk phenotypes. In this study, we implement a multivariate extension to the IWAS model, namely MV-IWAS, to consistently estimate and test for the causal effects of multiple brain imaging endophenotypes from the Alzheimer's Disease Neuroimaging Initiative (ADNI) in the presence of pleiotropic and possibly correlated SNPs. We further extend MV-IWAS to incorporate variant-specific direct effects on AD, analogous to the existing Egger regression Mendelian Randomization approach, which allows for testing of remaining pleiotropy after adjusting for multiple intermediate pathways. We propose a convenient approach for implementing MV-IWAS that solely relies on publicly available GWAS summary data and a reference panel. Through simulations with either individual-level or summary data, we demonstrate the well controlled Type I errors and superior power of MV-IWAS over UV-IWAS in the presence of pleiotropic SNPs. We apply the summary statistic based tests to 1578 heritable imaging derived phenotypes (IDPs) from the UK Biobank. MV-IWAS detected numerous IDPs as possible false positives by UV-IWAS while uncovering many additional causal neuroimaging phenotypes in AD which are strongly supported by the existing literature.

The Human Immunopeptidome Project: A Roadmap to Predict and Treat Immune Diseases.

The science that investigates the ensembles of all peptides associated to human leukocyte antigen (HLA) molecules is termed "immunopeptidomics" and is typically driven by mass spectrometry (MS) technologies. Recent advances in MS technologies, neoantigen discovery and cancer immunotherapy have catalyzed the launch of the Human Immunopeptidome Project (HIPP) with the goal of providing a complete map of the human immunopeptidome and making the technology so robust that it will be available in every clinic. Here, we provide a long-term perspective of the field and we use this framework to explore how we think the completion of the HIPP will truly impact the society in the future. In this context, we introduce the concept of immunopeptidome-wide association studies (IWAS). We highlight the importance of large cohort studies for the future and how applying quantitative immunopeptidomics at population scale may provide a new look at individual predisposition to common immune diseases as well as responsiveness to vaccines and immunotherapies. Through this vision, we aim to provide a fresh view of the field to stimulate new discussions within the community, and present what we see as the key challenges for the future for unlocking the full potential of immunopeptidomics in this era of precision medicine.

Imaging-wide association study: Integrating imaging endophenotypes in GWAS.

A new and powerful approach, called imaging-wide association study (IWAS), is proposed to integrate imaging endophenotypes with GWAS to boost statistical power and enhance biological interpretation for GWAS discoveries. IWAS extends the promising transcriptome-wide association study (TWAS) from using gene expression endophenotypes to using imaging and other endophenotypes with a much wider range of possible applications. As illustration, we use gray-matter volumes of several brain regions of interest (ROIs) drawn from the ADNI-1 structural MRI data as imaging endophenotypes, which are then applied to the individual-level GWAS data of ADNI-GO/2 and a large meta-analyzed GWAS summary statistics dataset (based on about 74,000 individuals), uncovering some novel genes significantly associated with Alzheimer's disease (AD). We also compare the performance of IWAS with TWAS, showing much larger numbers of significant AD-associated genes discovered by IWAS, presumably due to the stronger link between brain atrophy and AD than that between gene expression of normal individuals and the risk for AD. The proposed IWAS is general and can be applied to other imaging endophenotypes, and GWAS individual-level or summary association data.