Citations

Abstract Genetic studies have significantly advanced our understanding of tauopathies, yet the genetic aetiology of Pick’s disease, a rare 3-Repeat tauopathy, remains unclear. The MAPT p.A152T variant has been identified as a risk factor for Alzheimer’s disease and progressive supranuclear palsy, but its role in Pick’s disease is unknown. In this study, we examined the prevalence of MAPT p.A152T in the largest series of neuropathologically confirmed Pick’s disease cases to date (n = 401). Through genotyping, we identified a single mutation carrier in the Pick’s disease cohort (minor allele frequency = 0.12%). We previously reported MAPT p.A152T at a 0.20% frequency in healthy controls (n = 2456), suggesting that it does not associate with 3-Repeat tauopathy risk. To further investigate the effect of the variant on MAPT transcript expression, we used bulk RNA sequencing in Alzheimer’s disease and progressive supranuclear palsy A152T mutation carriers. We did not detect significant differences in 4-Repeat tau levels, though preliminary trends may indicate more nuanced effects that need to be examined with long-read sequencing in a larger series. Overall, our study suggests that MAPT p.A152T does not increase Pick’s disease risk and may instead be linked to 4-Repeat or mixed tau pathologies, warranting further functional investigation.

ABSTRACT This case highlights the diagnostic challenges posed by rare oropharyngeal neurofibromas, their potential to mimic other conditions, and the novel application of transoral robotic surgery (TORS) for the management of an oropharyngeal neurofibroma. A 47‐year‐old female presented with a 1‐year history of a left tonsillar mass. Clinical evaluation, imaging, and biopsy results were inconclusive but raised suspicion for a neoplasm. The patient underwent robotic‐assisted tonsillectomy and mass resection. Subsequent histopathological evaluation confirmed a benign spindle cell tumor consistent with neurofibroma. Oropharyngeal neurofibromas may present diagnostic challenges due to their resemblance to common tonsillar pathologies. Imaging and biopsies may not always provide definitive diagnoses, necessitating surgical excision for accurate characterization. This case demonstrates the utility of TORS, offering improved visualization and access while minimizing patient morbidity.

Abstract Accurate taxonomic profiling of human microbiomes is essential for advancing research and understanding the complex role microbial communities play in human health. When using shotgun metagenomics, the sequencing data is analyzed through metagenomic pipelines, which incorporate various open-source tools and classify microbes based on matched paired-end DNA reads. However, differences in sequencing and computational approaches can produce substantially different microbiome profiles from the same sample, making validation critical. One approach for validation is benchmarking with realistic mock communities, but this remains relatively rare. Additionally, existing benchmarks often overlook microbiome variability across life stages and body sites, limiting their clinical and research utility. Here, we developed age- and body site-stratified synthetic metagenomes, enabling context-aware benchmarking of microbiome pipelines. Using novelty-based sampling to prioritize microbial diversity and minimize redundancy among selected samples, we selected 300 representative, real biological samples spanning six categories: adult, child, toddler, and infant (>6 months and <6 months) gut samples, as well as adult vaginal samples. We validated three pipelines, Tiny Health’s proprietary Metagenomic Classifier v2 (THMCv2), MetaPhlAn4, and Kraken2+Bracken, using precision, recall, F1 score, and area under the precision-recall curve (AUPR) across age groups and sample types. THMCv2 demonstrated higher recall and F1 scores, detecting more taxa across sample types and ages, while MetaPhlAn4 achieved the highest precision. THMCv2 also achieved the highest area under the precision-recall curve, reflecting peak performance across both abundant and rare species. When analyses were weighted by abundance, THMCv2 and MetaPhlAn4 each characterized the mock community nearly perfectly. Errors for THMCv2 were largely restricted to very low-abundance taxa (<0.001%), whereas MetaPhlAn4 occasionally produced false positives for higher-abundance taxa. Species-level analyses of clinically relevant microbes confirmed these patterns, with THMCv2 demonstrating higher sensitivity, MetaPhlAn4 higher specificity, and Kraken2 lower overall performance. These results demonstrate clear precision-recall trade-offs in metagenomic profiling. This benchmarking framework provides a reproducible approach for evaluating pipeline performance across diverse microbiome contexts and life stages.

ABSTRACT Background Experiencing weight stigmatization is linked to maladaptive eating, poorer mental health, and increased risk of weight gain, potentially impacting metabolic bariatric surgery (MBS) outcomes. This meta‐analysis aimed to synthesize patient experiences of weight stigmatization before and after MBS and to examine the association of presurgical weight stigma on postsurgical weight loss. Methods This preregistered study followed PRISMA guidelines. Six databases were searched through March 2025; eligible studies included published articles and dissertations/theses available in English that quantitatively measured presurgical weight stigma among MBS samples and included relevant outcomes. Meta‐analyses utilized random effects models with change scores converted to Hedge's g and associations between presurgical experienced weight stigma and post‐MBS weight change converted to coefficient r . Results Forty‐one studies were included, with 36 reporting on experienced weight stigma change pre‐ to post‐MBS and 10 studies reporting on the relationship between pre‐MBS experienced weight stigma and post‐MBS weight loss. Conclusions Results revealed weight stigmatization decreased substantially after MBS (6–12 months, g = 1.28; 13–24 months, g = 1.16; 25–36 months, g = 1.26). Presurgical weight stigma was not associated with weight loss post‐surgery ( r = 0.05). Findings are limited by minimal studies reporting on longer term relationships between baseline stigma, post‐MBS weight loss, and additional health outcomes.

Breast size changes are common, but the underlying cause may be challenging to diagnose and requires a structured approach combining patient history, physical examination, and multimodality imaging to differentiate benign from malignant causes and improve patient outcomes.

ABSTRACT Background This study aimed to explore the effect of family history (FH) and polygenic risk scores (PRS) for multiple psychiatric disorders on lithium response in bipolar disorder (BD). Method The sample included patients from the Mayo Clinic BD Biobank. FH in first‐degree relatives was obtained via the patient questionnaire. Linear regression models tested the association of FH and PRS for BD, major depressive disorder (MDD), schizophrenia (SCZ), alcohol use disorder (AUD), anxiety disorder (ANX), and attention‐deficit/hyperactivity disorder (ADHD) with lithium response measured by the Alda A score adjusted for the Alda B sum score. Post hoc models additionally adjusted for clinical covariates (age at onset, rapid cycling, and BD subtype). Results 716 patients had Alda scores for lithium response (61.9% females, mean age = 43.4 years). FH‐BD ( β = −0.57, p = 0.015), AUD ( β = −0.44, p = 0.045), and ANX ( β = −0.61, p = 0.050) were associated with worse lithium response. After adjusting for clinical covariates, associations for FH‐BD and FH‐ANX were no longer significant. PRS‐BD was associated with better response ( β = 0.22, p = 0.041), while PRS‐MDD ( β = −0.28, p = 0.01) and PRS‐ADHD ( β = −0.24, p = 0.028) were associated with worse response, with effects largely unchanged after adjusting for clinical covariates. In the combined model considering all FHs simultaneously, only FH‐BD remained significantly associated with worse lithium response ( β = −0.71, p = 0.039). In the combined model for PRS, only PRS‐BD ( β = 0.31, p = 0.008; better response) and PRS‐MDD ( β = −0.29, p = 0.020; worse response) showed significant associations. Conclusions In this exploratory study, FH‐BD, AUD, and ANX were associated with poor response, though only FH‐AUD remained significant after adjusting for clinical factors. PRS‐BD predicted better response, while PRS‐MDD was associated with worse response. These findings suggest independent and potentially complementary roles of FH and PRS. Integrating both familial and genetic risk measures may improve personalized treatment strategies and outcomes for BD patients.