Exploring spatial heterogeneity in factors associated with injury severity in speeding-related crashes: An integrated machine learning and spatial modeling approach.

Speeding, a risky act of driving a vehicle at a speed exceeding the posted limit, has consistently emerged as a leading contributor to traffic fatalities. Identifying the risk factors associated with injury severity in speeding-related crashes is essential for implementing countermeasures aimed at preventing severe injury incidents and achieving Vision Zero goals. With the wealth of traffic crash data collected by various agencies, researchers have a valuable opportunity to conduct data-driven studies and employ various modeling methods to gain insights into the correlated factors affecting injury severity in traffic crashes. Machine learning models, owing to their superior predictive power compared to statistical models, are increasingly being adopted by researchers. These models, in conjunction with interpretation techniques, can reveal potential relationships between crash injury severity and contributing factors. Traffic crashes are inherently tied to geographic locations, distributed across road networks influenced by diverse socioeconomic and geographical factors. Recognizing spatial heterogeneity in traffic safety is crucial for tailored safety measures to address speeding-related crashes, as a one-size-fits-all approach may not work effectively everywhere. However, most existing machine learning models are unable to incorporate the spatial dependency among observations, such as traffic crashes, which hinders their ability to uncover spatial heterogeneity in traffic safety. To address this gap, this study introduces the Geographically Weighted Neural Network (GWNN) model, a spatial machine-learning model that integrates neural network (NN) and geographically weighted modeling approaches to investigate spatial heterogeneity in speeding-related crashes. Unlike the traditional NN model, which trains a single set of model parameters for all observations, the GWNN trains a local NN model for each crash location using a spatially weighted subsample of nearby crashes, allowing for the quantification of corresponding local effects of features through calculating local marginal effects. To understand the spatial heterogeneity in speeding-related crashes, this study extracted two years (2020 and 2021) of speeding-related crash data from Alabama for the development of the GWNN local models. The modeling results show significant spatial variability among several factors contributing to injury severity in speeding-related crashes. These factors include driver condition, vehicle type, crash type, speed limit, weather, crash time and location, roadway alignment, and traffic volume. Based on the GWNN modeling results, this study identified three types of spatial variations in relationships between contributing factors and crash injury severity: consistent positive associations, consistent negative associations, and inverse associations (i.e., marginal effects can vary between positive and negative depending on the location). This study contributes by integrating advanced machine learning and spatial modeling approaches to uncover intricate spatial patterns and factors influencing injury severity in speeding-related crashes, thereby facilitating the development of targeted policy implementations and safety interventions.

AI-based histopathology image analysis reveals a distinct subset of endometrial cancers.

Endometrial cancer (EC) has four molecular subtypes with strong prognostic value and therapeutic implications. The most common subtype (NSMP; No Specific Molecular Profile) is assigned after exclusion of the defining features of the other three molecular subtypes and includes patients with heterogeneous clinical outcomes. In this study, we employ artificial intelligence (AI)-powered histopathology image analysis to differentiate between p53abn and NSMP EC subtypes and consequently identify a sub-group of NSMP EC patients that has markedly inferior progression-free and disease-specific survival (termed 'p53abn-like NSMP'), in a discovery cohort of 368 patients and two independent validation cohorts of 290 and 614 from other centers. Shallow whole genome sequencing reveals a higher burden of copy number abnormalities in the 'p53abn-like NSMP' group compared to NSMP, suggesting that this group is biologically distinct compared to other NSMP ECs. Our work demonstrates the power of AI to detect prognostically different and otherwise unrecognizable subsets of EC where conventional and standard molecular or pathologic criteria fall short, refining image-based tumor classification. This study's findings are applicable exclusively to females.

Strangulated Indirect Inguinal Hernia-Containing Bladder: A Case Report.

Inguinal hernias involving the bladder are exceedingly rare and pose a diagnostic challenge. Identifying bladder involvement within an inguinal hernia is imperative to avoid iatrogenic bladder injuries and subsequent complications. Here we discuss a case of inguinal bladder herniation and bladder visualization using methylene blue dye intraoperatively. We present a case of a 45-year-old male who presented with a six-hour history of dysuria and a painful non-reducible right-sided groin mass that had previously been reducible for 17 years. Computed tomography demonstrated an irreducible indirect inguinal hernia-containing bladder. Open Lichtenstein repair was performed, and intraoperative methylene blue-dyed saline successfully identified the herniated bladder, preventing iatrogenic bladder injury. This case report demonstrates the importance of preoperative imaging and intraoperative visualization for the prevention of complications in a rare occurrence of a strangulated indirect inguinal hernia-containing bladder.

It is time to reconsider the use of naturally-occurring endotoxins in endotoxin recovery studies: Part 2 of a BioPhorum harmonized endotoxin recovery study.

The evaluation of Naturally Occurring Endotoxins (NOEs) for Low Endotoxin Recovery (LER) studies has been a topic in the industry and regulatory agencies have been hesitant to endorse NOE use in LER studies over purified Lipopolysaccharide (LPS) standards such as Control Standard Endotoxin (CSE) or Reference Standard Endotoxin (RSE). In a recent study involving 11 BioPhorum member companies across 13 sites, NOEs prepared in high and low nutrient conditions were evaluated in two common monoclonal antibody buffer formulations: 10 mM Sodium Citrate, 0.05 % Polysorbate 80, pH 6.0 and 20 mM Histidine, 0.05 % Polysorbate 80, pH 6.0. 12 g-negative bacterial isolates were used to prepare NOE analytes, which were spiked into the formulation buffers. Additionally, the NOEs were spiked into Limulus Amebocyte Lysate (LAL) reagent water as controls and purified LPS into the citrate/polysorbate buffer as the LER control. Results showed the average of three runs per organism was >50 % recovery, at the conclusion of the 7-day period, regardless of nutrient culture preparation conditions. Furthermore, purified LPS controls became undetectable (<50 % recovery) in the citrate/polysorbate buffer, highlighting the presence of LER. These findings highlight the potential value of using NOEs from relevant manufacturing facilities to assess overall risk when purified LPS recovery is insufficient.

Expanded genetic testing in familial hypercholesterolemia-A single center's experience.

Objective: Assess the yield of genetic testing for pathogenic variants in ABCG5, ABCG8, LIPA, and APOE in individuals with personal and family histories suggestive of familial hypercholesterolemia. Methods: Retrospective review of patients seen in the Advanced Lipid Disorders Clinic at Johns Hopkins. Results: In the lipid clinic at a single center during the years 2015-2023, 607 patients underwent genetic testing for familial hypercholesterolemia, of which 263 underwent the expanded genetic testing for sitosterolemia. Eighty-eight patients had genetic testing which included APOE, and 22 patients had testing which included LIPA. Among these, one patient was identified to have a pathogenic variant in APOE and another patient with a pathogenic variant in ABCG5 (0.7 % yield). The frequency of a positive result was double that of a variant of uncertain significance. Conclusion: These data suggest in rare cases expanded testing can provide answers for patients and families with a minimal likelihood of a variant of uncertain significance.

Supplementation with soluble or insoluble rice-bran fibers increases short-chain fatty acid producing bacteria in the gut microbiota in vitro.

Introduction: Studies have shown that a diet high in fiber and prebiotics has a positive impact on human health due largely to the fermentation of these compounds by the gut microbiota. One underutilized source of fiber may be rice bran, a waste product of rice processing that is used most frequently as an additive to livestock feed but may be a good source of fibers and other phenolic compounds as a human diet supplement. Previous studies focused on specific compounds extracted from rice bran showed that soluble fibers extracted from rice bran can improve glucose response and reduce weight gain in mouse models. However, less is known about changes in the human gut microbiota in response to regular rice bran consumption. Methods: In this study, we used a Simulator of the Human Intestinal Microbial Ecology (SHIME®) to cultivate the human gut microbiota of 3 different donors in conditions containing either soluble or insoluble fiber fractions from rice bran. Using 16S rRNA amplicon sequencing and targeted metabolomics via Gas Chromatography-Mass Spectrometry, we explored how gut microbial communities developed provided different supplemental fiber sources. Results: We found that insoluble and soluble fiber fractions increased short-chain fatty acid production, indicating that both fractions were fermented. However, there were differences in response between donors, for example the gut microbiota from donor 1 increased acetic acid production with both fiber types compared with control; whereas for donors 2 and 3, butanoic acid production increased with ISF and SF supplementation. Both soluble and insoluble rice bran fractions increased the abundance of Bifidobacterium and Lachnospiraceae taxa. Discussion: Overall, analysis of the effect of soluble and insoluble rice bran fractions on the human in vitro gut microbiota and the metabolites produced revealed individually variant responses to these prebiotics.

Whole genome and transcriptome integrated analyses guide clinical care of pediatric poor prognosis cancers.

The role for routine whole genome and transcriptome analysis (WGTA) for poor prognosis pediatric cancers remains undetermined. Here, we characterize somatic mutations, structural rearrangements, copy number variants, gene expression, immuno-profiles and germline cancer predisposition variants in children and adolescents with relapsed, refractory or poor prognosis malignancies who underwent somatic WGTA and matched germline sequencing. Seventy-nine participants with a median age at enrollment of 8.8 y (range 6 months to 21.2 y) are included. Germline pathogenic/likely pathogenic variants are identified in 12% of participants, of which 60% were not known prior. Therapeutically actionable variants are identified by targeted gene report and whole genome in 32% and 62% of participants, respectively, and increase to 96% after integrating transcriptome analyses. Thirty-two molecularly informed therapies are pursued in 28 participants with 54% achieving a clinical benefit rate; objective response or stable disease ≥6 months. Integrated WGTA identifies therapeutically actionable variants in almost all tumors and are directly translatable to clinical care of children with poor prognosis cancers.

Substance Use Within Trials of Psychological Interventions for Psychosis: Sample Inclusion, Secondary Measures, and Intervention Effectiveness.

INTRODUCTION: Current clinical guidelines recommend that patients with co-occurring psychosis and alcohol or substance use disorders (A/SUD) receive evidenced-based treatment for both disorders, including psychological intervention for psychosis. However, the efficacy of such treatments for individuals with co-occurring psychosis and A/SUD is unclear. STUDY DESIGN: Randomized controlled trials (RCTs) of psychological interventions for psychosis were systematically reviewed, to investigate how alcohol and substance use has been accounted for across sample inclusion and secondary measures. Findings from trials including individuals with co-occurring alcohol or substance use issues were then narratively summarized using the Synthesis Without Meta-Analysis guidelines, to indicate the overall efficacy of psychological interventions for psychosis, for this comorbid population. STUDY RESULTS: Across the 131 trials identified, 60.3% of trials excluded individuals with alcohol or substance use issues. Additionally, only 6.1% measured alcohol or substance use at baseline, while only 2.3% measured alcohol or substance use as a secondary outcome. Across trials explicitly including individuals with alcohol or substance use issues, insufficient evidence was available to conclude the efficacy of any individual psychological intervention. However, preliminary findings suggest that psychoeducation (PE) and metacognitive therapy (MCT) may be proposed for further investigation. CONCLUSION: Overall, co-occurring alcohol and substance use issues have been largely neglected across the recent RCTs of psychological interventions for psychosis; highlighting the challenges of making treatment decisions for these individuals using the current evidence base.

VOLTA: an enVironment-aware cOntrastive ceLl represenTation leArning for histopathology.

In clinical oncology, many diagnostic tasks rely on the identification of cells in histopathology images. While supervised machine learning techniques necessitate the need for labels, providing manual cell annotations is time-consuming. In this paper, we propose a self-supervised framework (enVironment-aware cOntrastive cell represenTation learning: VOLTA) for cell representation learning in histopathology images using a technique that accounts for the cell's mutual relationship with its environment. We subject our model to extensive experiments on data collected from multiple institutions comprising over 800,000 cells and six cancer types. To showcase the potential of our proposed framework, we apply VOLTA to ovarian and endometrial cancers and demonstrate that our cell representations can be utilized to identify the known histotypes of ovarian cancer and provide insights that link histopathology and molecular subtypes of endometrial cancer. Unlike supervised models, we provide a framework that can empower discoveries without any annotation data, even in situations where sample sizes are limited.

Exploring the lived experiences and care challenges of formal paid caregivers for people with intellectual disability and dementia.

A greater number of people with intellectual disability are living into older age and are at increased risk of developing conditions such as dementia. Caring for a person with dementia presents several challenges for formal caregivers due to the progressive nature of the disease. An interpretive phenomenological analysis was used to understand the lived experiences of a purposive sample of formal caregivers in caring for people with intellectual disability and dementia. Discussions from 14 individual interviews generated data were analysed. Four key super-ordinate themes emerged which were: (1) recognising early indicators and diagnosis, (2) post diagnostic support, (3) coping with change and (4) need for future development. Themes reflected the experiences, barriers to dementia diagnosis and provide a valuable insight into the challenges faced by formal caregivers in providing aged care services.

Understanding the Impacts of Online Mental Health Peer Support Forums: Realist Synthesis.

BACKGROUND: Online forums are widely used for mental health peer support. However, evidence of their safety and effectiveness is mixed. Further research focused on articulating the contexts in which positive and negative impacts emerge from forum use is required to inform innovations in implementation. OBJECTIVE: This study aimed to develop a realist program theory to explain the impacts of online mental health peer support forums on users. METHODS: We conducted a realist synthesis of literature published between 2019 and 2023 and 18 stakeholder interviews with forum staff. RESULTS: Synthesis of 102 evidence sources and 18 interviews produced an overarching program theory comprising 22 context-mechanism-outcome configurations. Findings indicate that users' perceptions of psychological safety and the personal relevance of forum content are foundational to ongoing engagement. Safe and active forums that provide convenient access to information and advice can lead to improvements in mental health self-efficacy. Within the context of welcoming and nonjudgmental communities, users may benefit from the opportunity to explore personal difficulties with peers, experience reduced isolation and normalization of mental health experiences, and engage in mutual encouragement. The program theory highlights the vital role of moderators in creating facilitative online spaces, stimulating community engagement, and limiting access to distressing content. A key challenge for organizations that host mental health forums lies in balancing forum openness and anonymity with the need to enforce rules, such as restrictions on what users can discuss, to promote community safety. CONCLUSIONS: This is the first realist synthesis of online mental health peer support forums. The novel program theory highlights how successful implementation depends on establishing protocols for enhancing safety and strategies for maintaining user engagement to promote forum sustainability. TRIAL REGISTRATION: PROSPERO CRD42022352528; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=352528.

The Types of Psychosocial Factors Associated with Suicidality Outcomes for People Living with Bipolar Disorder: A Scoping Review.

Bipolar Disorder is associated with high rates of suicidal thoughts, behaviors, and outcomes, yet the lived experience of suicidality and Bipolar Disorder is not particularly well understood. Understanding the role of psychosocial aetiologies in suicidality outcomes for those living with Bipolar Disorder is key for developing appropriately targeted interventions focusing on factors that are amenable to change. In line with PRISMA guidance, we conducted a scoping review to identify the types of psychosocial factors studied in relation to the experience of suicidality for people living with Bipolar Disorder diagnoses. Systematic literature searches identified a sample of 166 articles from which key study data were extracted and charted. A narrative synthesis of the reviewed literature is presented ordered by the factors investigated across studies, a frequency count of the types of psychological/social aetiologies studied, and a brief overview of the key findings for each aetiology. Most of the identified literature took the form of quantitative cross-sectional studies, with only one qualitative study and 18 quantitative prospective studies. The most studied aetiologies were trauma (specifically early adverse experiences and childhood traumas) and stressful life events, impulsivity (primarily subjective self-reported trait impulsivity), social support and functioning, and personality/temperament factors. Only six studies in the final sample reported basing their research questions and/or hypotheses on an explicit theoretical model of suicide. The literature was primarily focused on using self-report measurements of key aetiologies and on factors which lead to worsened suicidality rather than focusing on potentially protective or buffering factors. Future research needs to better justify the aetiologies investigated in relation to suicidality outcomes for people living with Bipolar Disorder, including a firmer basis in theory and hypothesis testing, more prospective designs, and the use of alternative assessments of psychosocial aetiologies in addition to self-report questionnaires.

GlycA Levels Independently Predict Coronary Artery Calcium Incidence and Progression in the ELSA-Brasil Cohort (Brazilian Longitudinal Study of Adult Health).

Atherosclerosis is an inflammatory disease. Coronary artery calcium (CAC) is a marker of atherosclerotic disease events and mortality risk. Increased GlycA, an emerging marker of inflammation, is associated with a higher risk for coronary artery disease (CAD). However, there is conflicting evidence on whether GlycA predicts subclinical CAD progression. We hypothesized that GlycA can predict subclinical CAC incidence/progression in healthy participants. We included 2,690 ELSA-Brasil cohort participants without cardiovascular/chronic inflammatory disease not receiving statin therapy who had GlycA levels measured and 2 interval CAC assessments between 2010 and 2018. Multivariable logistic and linear regression models were computed to evaluate GlycA as a predictor of CAC incidence and progression. CAC incidence required a baseline CAC of 0. CAC progression required a baseline CAC >0. The mean age of participants was 48.6 ± 7.7 years, 56.7% were women, and 54.6% and 16.1% (429 of 2,690) were White and Black, respectively. The mean CAC interscan period was 5.1 ± 0.9 years, the mean GlycA level was 414.7 ± 65 µmol/L, and the incidence of CAC was 13.1% (280 of 2,129). The GlycA level odds ratio for CAC incidence was 1.002 (95% confidence interval 1.0005 to 1.005, p = 0.016), adjusted for demographics, lifestyle, a family history of early CAD (≤60 years), lipids, and co-morbidities. The GlycA (≤p25 vs ≥p75) odds ratio for CAC progression (Berry definition) was 1.77 (95% confidence interval 1.07 to 2.96, p = 0.03) in a similar multivariable-adjusted model. Higher GlycA levels were associated with CAC incidence and progression in a healthy Brazilian cohort.

The benefit of a complete reference genome for cancer structural variant analysis.

The complexities of cancer genomes are becoming more easily interpreted due to advancements in sequencing technologies and improved bioinformatic analysis. Structural variants (SVs) represent an important subset of somatic events in tumors. While detection of SVs has been markedly improved by the development of long-read sequencing, somatic variant identification and annotation remains challenging. We hypothesized that use of a completed human reference genome (CHM13-T2T) would improve somatic SV calling. Our findings in a tumour/normal matched benchmark sample and two patient samples show that the CHM13-T2T improves SV detection and prioritization accuracy compared to GRCh38, with a notable reduction in false positive calls. We also overcame the lack of annotation resources for CHM13-T2T by lifting over CHM13-T2T-aligned reads to the GRCh38 genome, therefore combining both improved alignment and advanced annotations. In this process, we assessed the current SV benchmark set for COLO829/COLO829BL across four replicates sequenced at different centers with different long-read technologies. We discovered instability of this cell line across these replicates; 346 SVs (1.13%) were only discoverable in a single replicate. We identify 49 somatic SVs, which appear to be stable as they are consistently present across the four replicates. As such, we propose this consensus set as an updated benchmark for somatic SV calling and include both GRCh38 and CHM13-T2T coordinates in our benchmark. The benchmark is available at: 10.5281/zenodo.10819636 Our work demonstrates new approaches to optimize somatic SV prioritization in cancer with potential improvements in other genetic diseases.

Exploration of Germline Correlates and Risk of Immune-Related Adverse Events in Advanced Cancer Patients Treated with Immune Checkpoint Inhibitors.

Immune checkpoint inhibitors (ICIs) are increasingly used in the treatment of many tumor types, and durable responses can be observed in select populations. However, patients may exhibit significant immune-related adverse events (irAEs) that may lead to morbidity. There is limited information on whether the presence of specific germline mutations may highlight those at elevated risk of irAEs. We evaluated 117 patients with metastatic solid tumors or hematologic malignancies who underwent genomic analysis through the ongoing Personalized OncoGenomics (POG) program at BC Cancer and received an ICI during their treatment history. Charts were reviewed for irAEs. Whole genome sequencing of a fresh biopsy and matched normal specimens (blood) was performed at the time of POG enrollment. Notably, we found that MHC class I alleles in the HLA-B27 family, which have been previously associated with autoimmune conditions, were associated with grade 3 hepatitis and pneumonitis (q = 0.007) in patients treated with combination PD-1/PD-L1 and CTLA-4 inhibitors, and PD-1 inhibitors in combination with IDO-1 inhibitors. These data highlight that some patients may have a genetic predisposition to developing irAEs.

Injury-severity analysis of crashes involving defective vehicles and accounting for the underlying socioeconomic mediators.

Crashes occur from a combination of factors related to the driver, roadway, and vehicle factors. The impact of vehicles on road crashes is a critical consideration within road safety analysis, even though not much studies have been conducted in this area. This study assessed how various vehicle and other crash factors are significantly associated with crash outcomes. To do this, historical vehicle defect-related crashes were obtained for the state of Alabama from 2016 to 2020. After data cleaning, a crash injury severity model was developed using the random parameters multinomial logit with heterogeneity in means approach to account for possible unobserved heterogeneity in the data. A spatial analysis was further conducted to better understand vehicle defect crashes as a broader societal issue and potentially explore their connection with the socio-demographic characteristics of the drivers of these vehicles. The preliminary data analysis showed that brake and tire defects accounted for about 65% of the vehicle defects associated with the crashes. The model estimation results revealed that improper tread depth and headlight defects were associated with major injury outcomes, while brake defects were more associated with minor injuries. Also, crashes associated with speeding, drunk driving, failure to use seatbelts, and those that occurred on curved roads left with downgrades were likely to result in major injuries. Findings from the spatial analysis showed that postal codes with higher median incomes are more likely to record lower vehicle defect-related crashes, unlike those that have higher proportions of females and African Americans. The study's findings provide data-driven evidence for sustained safety campaigns, workshops, and training on basic vehicle maintenance practices in the low-income communities in the state.

Canadian COVID-19 host genetics cohort replicates known severity associations.

The HostSeq initiative recruited 10,059 Canadians infected with SARS-CoV-2 between March 2020 and March 2023, obtained clinical information on their disease experience and whole genome sequenced (WGS) their DNA. We analyzed the WGS data for genetic contributors to severe COVID-19 (considering 3,499 hospitalized cases and 4,975 non-hospitalized after quality control). We investigated the evidence for replication of loci reported by the International Host Genetics Initiative (HGI); analyzed the X chromosome; conducted rare variant gene-based analysis and polygenic risk score testing. Population stratification was adjusted for using meta-analysis across ancestry groups. We replicated two loci identified by the HGI for COVID-19 severity: the LZTFL1/SLC6A20 locus on chromosome 3 and the FOXP4 locus on chromosome 6 (the latter with a variant significant at P < 5E-8). We found novel significant associations with MRAS and WDR89 in gene-based analyses, and constructed a polygenic risk score that explained 1.01% of the variance in severe COVID-19. This study provides independent evidence confirming the robustness of previously identified COVID-19 severity loci by the HGI and identifies novel genes for further investigation.

Designing a Library of Lived Experience for Mental Health: integrated realist synthesis and experience-based co-design study in UK mental health services.

OBJECTIVE: Living Library events involve people being trained as living 'Books', who then discuss aspects of their personal experiences in direct conversation with attendees, referred to as 'Readers'. This study sought to generate a realist programme theory and a theory-informed implementation guide for a Library of Lived Experience for Mental Health (LoLEM). DESIGN: Integrated realist synthesis and experience-based co-design. SETTING: Ten online workshops with participants based in the North of England. PARTICIPANTS: Thirty-one participants with a combination of personal experience of using mental health services, caring for someone with mental health difficulties and/or working in mental health support roles. RESULTS: Database searches identified 30 published and grey literature evidence sources which were integrated with data from 10 online co-design workshops conducted over 12 months. The analysis generated a programme theory comprising five context-mechanism-outcome (CMO) configurations. Findings highlight how establishing psychological safety is foundational to productive Living Library events (CMO 1). For Readers, direct conversations humanise others' experiences (CMO 2) and provide the opportunity to flexibly explore new ways of living (CMO 3). Through participation in a Living Library, Books may experience personal empowerment (CMO 4), while the process of self-authoring and co-editing their story (CMO 5) can contribute to personal development. This programme theory informed the co-design of an implementation guide highlighting the importance of tailoring event design and participant support to the contexts in which LoLEM events are held. CONCLUSIONS: The LoLEM has appeal across stakeholder groups and can be applied flexibly in a range of mental health-related settings. Implementation and evaluation are required to better understand the positive and negative impacts on Books and Readers. TRIAL REGISTRATION NUMBER: PROSPERO CRD42022312789.

Mitofusin 2 Variant Presenting With a Phenotype of Multiple System Atrophy of Cerebellar Subtype.

Objectives: To investigate the etiology of cerebellar ataxia in an adult male patient. Methods: We performed standard neurologic assessment and genome sequencing of a 62-year-old man with rapidly progressive balance and gait abnormalities. Results: The propositus exhibited cognitive dysfunction, mild appendicular bradykinesia, prominent appendicular ataxia, dysarthria, and hypomimia with minimal dysautonomic symptoms. Nerve conduction studies showed mild peripheral sensory neuropathy and normal motor nerve conduction velocities. Brain imaging showed progressive cerebellar atrophy and gliosis of the olivopontocerebellar fibers, characterized by T2 hyperintensity within the pons. Genetic testing revealed a likely pathogenic germline variant in MFN2 (NM_014874: c.[838C>T];[=], p.(R280C)) in the GTPase domain (G) interface; pathogenic variants of MFN2 typically cause hereditary sensory and motor neuropathy VI or Charcot-Marie-Tooth disease 2A. The presence of progressive ataxia, "hot cross bun" sign, and dysautonomia has been associated with multiple system atrophy, cerebellar type (MSA-C). Discussion: We describe progressive cerebellar ataxia in an individual with a deleterious variant in MFN2. Our findings suggest that pathogenic variants in MFN2 can result in a spectrum of phenotypes including cerebellar ataxia with cerebellar-pontine atrophy in the absence of significant neuropathy and in a manner closely resembling MSA-C.