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Article: Narrative Review of Machine Learning in Rheumatic and Musculoskeletal Diseases for Clinicians and Researchers: Biases, Goals, and Future Directions.

Nelson, Amanda E / Arbeeva, Liubov

2022 Volume 49, Issue 11, Page(s) 1191–1200

Abstract: There has been rapid growth in the use of artificial intelligence (AI) analytics in medicine in recent years, including in rheumatic and musculoskeletal diseases (RMDs). Such methods represent a challenge to clinicians, patients, and researchers, given ... ...

Abstract	There has been rapid growth in the use of artificial intelligence (AI) analytics in medicine in recent years, including in rheumatic and musculoskeletal diseases (RMDs). Such methods represent a challenge to clinicians, patients, and researchers, given the "black box" nature of most algorithms, the unfamiliarity of the terms, and the lack of awareness of potential issues around these analyses. Therefore, this review aims to introduce this subject area in a way that is relevant and meaningful to clinicians and researchers. We hope to provide some insights into relevant strengths and limitations, reporting guidelines, as well as recent examples of such analyses in key areas, with a focus on lessons learned and future directions in diagnosis, phenotyping, prognosis, and precision medicine in RMDs.
MeSH term(s)	Humans ; Artificial Intelligence ; Goals ; Machine Learning ; Musculoskeletal Diseases/diagnosis ; Bias
Language	English
Publishing date	2022-07-15
Publishing country	Canada
Document type	Journal Article ; Review ; Research Support, N.I.H., Extramural
ZDB-ID	194928-7
ISSN	1499-2752 ; 0315-162X
ISSN (online)	1499-2752
ISSN	0315-162X
DOI	10.3899/jrheum.220326
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Article ; Online: Machine Learning Approaches to the Prediction of Osteoarthritis Phenotypes and Outcomes.

Arbeeva, Liubov / Minnig, Mary C / Yates, Katherine A / Nelson, Amanda E

Current rheumatology reports

2023 Volume 25, Issue 11, Page(s) 213–225

Abstract: Purpose of review: Osteoarthritis (OA) is a complex heterogeneous disease with no effective treatments. Artificial intelligence (AI) and its subfield machine learning (ML) can be applied to data from different sources to (1) assist clinicians and ... ...

Abstract	Purpose of review: Osteoarthritis (OA) is a complex heterogeneous disease with no effective treatments. Artificial intelligence (AI) and its subfield machine learning (ML) can be applied to data from different sources to (1) assist clinicians and patients in decision making, based on machine-learned evidence, and (2) improve our understanding of pathophysiology and mechanisms underlying OA, providing new insights into disease management and prevention. The purpose of this review is to improve the ability of clinicians and OA researchers to understand the strengths and limitations of AI/ML methods in applications to OA research. Recent findings: AI/ML can assist clinicians by prediction of OA incidence and progression and by providing tailored personalized treatment. These methods allow using multidimensional multi-source data to understand the nature of OA, to identify different OA phenotypes, and for biomarker discovery. We described the recent implementations of AI/ML in OA research and highlighted potential future directions and associated challenges.
Language	English
Publishing date	2023-08-10
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	2057357-1
ISSN	1534-6307 ; 1523-3774
ISSN (online)	1534-6307
ISSN	1523-3774
DOI	10.1007/s11926-023-01114-9
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Article ; Online: Association of plasma microbial composition with a leaky gut in obesity-related osteoarthritis: An exploratory study.

Arbeeva, Liubov / Azcarate-Peril, M Andrea / Cui, Yang / Nelson, Amanda E / Loeser, Richard F

Osteoarthritis and cartilage open

2022 Volume 4, Issue 4, Page(s) 100317

Abstract: Objective: To examine the plasma microbiome for differences between obese individuals with and without osteoarthritis (OA) and its association with serum lipopolysaccharide (LPS).: Design: Blood samples from 70 participants with body mass index (BMI) ...

Abstract	Objective: To examine the plasma microbiome for differences between obese individuals with and without osteoarthritis (OA) and its association with serum lipopolysaccharide (LPS). Design: Blood samples from 70 participants with body mass index (BMI) ≥ 30kg/m2 and age ≥55 years, with (cases) or without (controls) hand plus knee OA, were analyzed for serum LPS and composition of the plasma microbiome. The Dirichlet-multinominal recursive partitioning model (DM-RPart) was applied to microbiome compositional data to test the hypothesis that LPS levels distinguish plasma microbiome, accounting for BMI and age. Results: No significant differences in alpha diversity, or compositional differences between groups at the genus level, were seen between cases and controls (p = 0.11). β-Diversity was significantly associated with serum LPS levels (p = 0.01). DM-RPart resulted in an optimal tree with 3 divisions: 1) based on age (split at 69 years); 2) those older than 69 were split based on BMI; 3) those with BMI <39 kg/m2 were split based on LPS level (at 65 EU/ml). This resulted in 4 groups (nodes 2, and 5-7). Participants in node 2 were younger and the majority had no or mild OA. Those in nodes 5 and 6 were comparable in age and BMI but node 6 had higher LPS and more severe OA. Individuals in node 7 were older, had higher BMI, and the most severe OA. Conclusions: Our results suggest a relationship between serum LPS and the plasma microbiome in a subgroup of obese individuals with hand plus knee OA that could reflect differences in intestinal permeability.
Language	English
Publishing date	2022-10-29
Publishing country	England
Document type	Journal Article
ISSN	2665-9131
ISSN (online)	2665-9131
DOI	10.1016/j.ocarto.2022.100317
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Article: Precision Medicine-Based Machine Learning Analyses to Explore Optimal Exercise Therapies for Individuals With Knee Osteoarthritis: Random Forest-Informed Tree-Based Learning.

Kim, Siyeon / Kosorok, Michael R / Arbeeva, Liubov / Schwartz, Todd A / Callahan, Leigh F / Golightly, Yvonne M / Nelson, Amanda E / Allen, Kelli D

The Journal of rheumatology

2023 Volume 50, Issue 10, Page(s) 1341–1345

Abstract: Objective: We applied a precision medicine-based machine learning approach to discover underlying patient characteristics associated with differential improvement in knee osteoarthritis symptoms following standard physical therapy (PT), internet-based ... ...

Abstract	Objective: We applied a precision medicine-based machine learning approach to discover underlying patient characteristics associated with differential improvement in knee osteoarthritis symptoms following standard physical therapy (PT), internet-based exercise training (IBET), and a usual care/wait list control condition. Methods: Participants (n = 303) were from the Physical Therapy vs Internet-Based Training for Patients with Knee Osteoarthritis trial. The primary outcome was the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) total score at 12-month follow-up. Random forest-informed tree-based learning was applied to identify patient characteristics that were critical to improving outcomes, and patients with those features were grouped. Results: Age, BMI, and Brief Fear of Movement (BFOM) score, all at baseline, were identified as characteristics that effectively divided participants, creating 6 subgroups. Assigning treatments according to these models, compared to assigning a single best treatment to all patients, resulted in greater improvements of the average WOMAC at 12 months ( Conclusion: These results suggest that easily assessed patient characteristics including age, fear of movement, and BMI could be used to guide patients toward either home-based exercise or PT, though additional studies are needed to confirm these findings. (ClinicalTrials.gov: NCT02312713).
MeSH term(s)	Humans ; Osteoarthritis, Knee/therapy ; Precision Medicine ; Random Forest ; Exercise Therapy/methods ; Exercise ; Treatment Outcome
Language	English
Publishing date	2023-08-01
Publishing country	Canada
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	194928-7
ISSN	1499-2752 ; 0315-162X
ISSN (online)	1499-2752
ISSN	0315-162X
DOI	10.3899/jrheum.2022-1039
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Article ; Online: Biclustering reveals potential knee OA phenotypes in exploratory analyses: Data from the Osteoarthritis Initiative.

Nelson, Amanda E / Keefe, Thomas H / Schwartz, Todd A / Callahan, Leigh F / Loeser, Richard F / Golightly, Yvonne M / Arbeeva, Liubov / Marron, J S

PloS one

2022 Volume 17, Issue 5, Page(s) e0266964

Abstract: Objective: To apply biclustering, a methodology originally developed for analysis of gene expression data, to simultaneously cluster observations and clinical features to explore candidate phenotypes of knee osteoarthritis (KOA) for the first time.: ... ...

Abstract	Objective: To apply biclustering, a methodology originally developed for analysis of gene expression data, to simultaneously cluster observations and clinical features to explore candidate phenotypes of knee osteoarthritis (KOA) for the first time. Methods: Data from the baseline Osteoarthritis Initiative (OAI) visit were cleaned, transformed, and standardized as indicated (leaving 6461 knees with 86 features). Biclustering produced submatrices of the overall data matrix, representing similar observations across a subset of variables. Statistical validation was determined using the novel SigClust procedure. After identifying biclusters, relationships with key outcome measures were assessed, including progression of radiographic KOA, total knee arthroplasty, loss of joint space width, and worsening Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores, over 96 months of follow-up. Results: The final analytic set included 6461 knees from 3330 individuals (mean age 61 years, mean body mass index 28 kg/m2, 57% women and 86% White). We identified 6 mutually exclusive biclusters characterized by different feature profiles at baseline, particularly related to symptoms and function. Biclusters represented overall better (#1), similar (#2, 3, 6), and poorer (#4, 5) prognosis compared to the overall cohort of knees, respectively. In general, knees in biclusters #4 and 5 had more structural progression (based on Kellgren-Lawrence grade, total knee arthroplasty, and loss of joint space width) but tended to have an improvement in WOMAC pain scores over time. In contrast, knees in bicluster #1 had less incident and progressive KOA, fewer total knee arthroplasties, less loss of joint space width, and stable pain scores compared with the overall cohort. Significance: We identified six biclusters within the baseline OAI dataset which have varying relationships with key outcomes in KOA. Such biclusters represent potential phenotypes within the larger cohort and may suggest subgroups at greater or lesser risk of progression over time.
MeSH term(s)	Disease Progression ; Female ; Humans ; Knee Joint/diagnostic imaging ; Knee Joint/surgery ; Male ; Osteoarthritis, Knee/genetics ; Osteoarthritis, Knee/surgery ; Pain ; Phenotype
Language	English
Publishing date	2022-05-24
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, Non-U.S. Gov't
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0266964
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Article ; Online: Application of Heterogeneity of Treatment-Effects Methods: Exploratory Analyses of a Trial of Exercise-Based Interventions for Knee Osteoarthritis.

Coffman, Cynthia J / Arbeeva, Liubov / Schwartz, Todd A / Callahan, Leigh F / Golightly, Yvonne M / Goode, Adam P / Huffman, Kim M / Allen, Kelli D

Arthritis care & research

2022 Volume 74, Issue 8, Page(s) 1359–1368

Abstract: Objective: To evaluate heterogeneity of treatment effects in a trial of exercise-based interventions for knee osteoarthritis (OA).: Methods: Participants (n = 350) were randomized to standard physical therapy (PT; n = 140), internet-based exercise ... ...

Abstract	Objective: To evaluate heterogeneity of treatment effects in a trial of exercise-based interventions for knee osteoarthritis (OA). Methods: Participants (n = 350) were randomized to standard physical therapy (PT; n = 140), internet-based exercise training (IBET; n = 142), or wait list (WL; n = 68) control. We applied qualitative interaction trees (QUINT), a sequential partitioning method, and generalized unbiased interaction detection and estimation (GUIDE), a regression tree approach, to identify subgroups with greater improvements in Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score over 4 months. Predictors included 24 demographic, clinical, and psychosocial characteristics. We conducted internal validation to estimate optimism (bias) in the range of mean outcome differences among arms. Results: Both QUINT and GUIDE indicated that for participants with lower body mass index (BMI), IBET was better than PT (improvements of WOMAC ranged from 6.3 to 9.1 points lower), and for those with higher BMI and a longer duration of knee OA, PT was better than IBET (WOMAC improvement was 6.3 points). In GUIDE analyses comparing PT or IBET to WL, participants not employed had improvements in WOMAC ranging from 1.8 to 6.8 points lower with PT or IBT versus WL. From internal validation, there were large corrections to the mean outcome differences among arms; however, after correction, some differences remained in the clinically meaningful range. Conclusion: Results suggest there may be subgroups who experience greater improvement in symptoms from PT or IBET, and this finding could guide referrals and future trials. However, uncertainty persists for specific treatment-effects size estimates and how they apply beyond this study sample.
MeSH term(s)	Exercise ; Humans ; Osteoarthritis, Knee/drug therapy ; Osteoarthritis, Knee/therapy ; Physical Therapy Modalities ; Research Design ; Time Factors
Language	English
Publishing date	2022-05-02
Publishing country	United States
Document type	Journal Article ; Randomized Controlled Trial ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, Non-U.S. Gov't
ZDB-ID	645059-3
ISSN	2151-4658 ; 0893-7524 ; 2151-464X
ISSN (online)	2151-4658
ISSN	0893-7524 ; 2151-464X
DOI	10.1002/acr.24564
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Article ; Online: CC-Chemokine Receptor-2 Expression in Osteoblasts Contributes to Cartilage and Bone Damage during Post-Traumatic Osteoarthritis.

Willcockson, Helen / Ozkan, Huseyin / Valdés-Fernández, José / Arbeeva, Liubov / Mucahit, Esra / Musawwir, Layla / Hooper, Lola B / Granero-Moltó, Froilán / Prósper, Felipe / Longobardi, Lara

Biomolecules

2023 Volume 13, Issue 6

Abstract: In osteoarthritis (OA), bone changes are radiological hallmarks and are considered important for disease progression. The C-C chemokine receptor-2 (CCR2) has been shown to play an important role in bone physiology. In this study, we investigated ... ...

Abstract	In osteoarthritis (OA), bone changes are radiological hallmarks and are considered important for disease progression. The C-C chemokine receptor-2 (CCR2) has been shown to play an important role in bone physiology. In this study, we investigated whether
MeSH term(s)	Mice ; Animals ; Osteophyte ; Receptors, CCR2/genetics ; Osteoarthritis/metabolism ; Cartilage, Articular/metabolism ; Bone and Bones/metabolism ; Pain ; Osteoblasts/metabolism ; Disease Progression
Chemical Substances	Receptors, CCR2
Language	English
Publishing date	2023-05-26
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
ZDB-ID	2701262-1
ISSN	2218-273X ; 2218-273X
ISSN (online)	2218-273X
ISSN	2218-273X
DOI	10.3390/biom13060891
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Article ; Online: Patterns of variation among baseline femoral and tibial cartilage thickness and clinical features: Data from the osteoarthritis initiative.

Keefe, Thomas H / Minnig, Mary Catherine / Arbeeva, Liubov / Niethammer, Marc / Xu, Zhenlin / Shen, Zhengyang / Chen, Boqi / Nissman, Daniel B / Golightly, Yvonne M / Marron, J S / Nelson, Amanda E

Osteoarthritis and cartilage open

2023 Volume 5, Issue 1, Page(s) 100334

Abstract: Objective: To employ novel methodologies to identify phenotypes in knee OA based on variation among three baseline data blocks: 1) femoral cartilage thickness, 2) tibial cartilage thickness, and 3) participant characteristics and clinical features.: ... ...

Abstract	Objective: To employ novel methodologies to identify phenotypes in knee OA based on variation among three baseline data blocks: 1) femoral cartilage thickness, 2) tibial cartilage thickness, and 3) participant characteristics and clinical features. Methods: Baseline data were from 3321 Osteoarthritis Initiative (OAI) participants with available cartilage thickness maps (6265 knees) and 77 clinical features. Cartilage maps were obtained from 3D DESS MR images using a deep-learning based segmentation approach and an atlas-based analysis developed by our group. Angle-based Joint and Individual Variation Explained (AJIVE) was used to capture and quantify variation, both Results: Three major modes of variation were shared across the three data blocks. Mode 1 reflected overall thicker cartilage among men, those with higher education, and greater knee forces; Mode 2 showed associations between worsening Kellgren-Lawrence Grade, medial cartilage thinning, and worsening symptoms; and Mode 3 contrasted lateral and medial-predominant cartilage loss associated with BMI and malalignment. Each data block also demonstrated individual, independent modes of variation consistent with the known discordance between symptoms and structure in knee OA and reflecting the importance of features such as physical function, symptoms, and comorbid conditions independent of structural damage. Conclusions: This exploratory analysis, combining the rich OAI dataset with novel methods for determining and visualizing cartilage thickness, reinforces known associations in knee OA while providing insights into the potential for data integration in knee OA phenotyping.
Language	English
Publishing date	2023-01-24
Publishing country	England
Document type	Journal Article
ISSN	2665-9131
ISSN (online)	2665-9131
DOI	10.1016/j.ocarto.2023.100334
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Article ; Online: Intestinal Helminth Infection Impairs Oral and Parenteral Vaccine Efficacy.

Zhang, Yugen / Hardy, LaKeya C / Kapita, Camille M / Hall, Jason A / Arbeeva, Liubov / Campbell, Evelyn / Urban, Joseph F / Belkaid, Yasmine / Nagler, Cathryn R / Iweala, Onyinye I

Journal of immunology (Baltimore, Md. : 1950)

2023 Volume 211, Issue 3, Page(s) 389–402

Abstract: The impact of endemic parasitic infection on vaccine efficacy is an important consideration for vaccine development and deployment. We have examined whether intestinal infection with the natural murine helminth Heligmosomoides polygyrus bakeri alters Ag- ... ...

Abstract	The impact of endemic parasitic infection on vaccine efficacy is an important consideration for vaccine development and deployment. We have examined whether intestinal infection with the natural murine helminth Heligmosomoides polygyrus bakeri alters Ag-specific Ab and cellular immune responses to oral and parenteral vaccination in mice. Oral vaccination of mice with a clinically relevant, live, attenuated, recombinant Salmonella vaccine expressing chicken egg OVA (Salmonella-OVA) induced the accumulation of activated, OVA-specific T effector cells rather than OVA-specific regulatory T cells in the GALT. Intestinal helminth infection significantly reduced Th1-skewed Ab responses to oral vaccination with Salmonella-OVA. Activated, adoptively transferred, OVA-specific CD4+ T cells accumulated in draining mesenteric lymph nodes of vaccinated mice, regardless of their helminth infection status. However, helminth infection increased the frequencies of adoptively transferred OVA-specific CD4+ T cells producing IL-4 and IL-10 in the mesenteric lymph node. Ab responses to the oral Salmonella-OVA vaccine were reduced in helminth-free mice adoptively transferred with OVA-specific CD4+ T cells harvested from mice with intestinal helminth infection. Intestinal helminth infection also significantly reduced Th2-skewed Ab responses to parenteral vaccination with OVA adsorbed to alum. These findings suggest that vaccine-specific CD4+ T cells induced in the context of helminth infection retain durable immunomodulatory properties and may promote blunted Ab responses to vaccination. They also underscore the potential need to treat parasitic infection before mass vaccination campaigns in helminth-endemic areas.
MeSH term(s)	Mice ; Animals ; Vaccine Efficacy ; Helminthiasis ; Intestinal Diseases, Parasitic ; CD4-Positive T-Lymphocytes ; Vaccines, Synthetic ; Ovalbumin ; Mice, Inbred BALB C
Chemical Substances	Vaccines, Synthetic ; Ovalbumin (9006-59-1)
Language	English
Publishing date	2023-05-22
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
ZDB-ID	3056-9
ISSN	1550-6606 ; 0022-1767 ; 1048-3233 ; 1047-7381
ISSN (online)	1550-6606
ISSN	0022-1767 ; 1048-3233 ; 1047-7381
DOI	10.4049/jimmunol.2300084
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Article ; Online: Accelerometer-Based Physical Activity Patterns and Associations With Outcomes Among Individuals With Osteoarthritis.

Beauchamp, Tyler / Arbeeva, Liubov / Cleveland, Rebecca J / Golightly, Yvonne M / Hales, Derek P / Hu, David G / Allen, Kelli D

Journal of clinical rheumatology : practical reports on rheumatic & musculoskeletal diseases

2021 Volume 28, Issue 2, Page(s) e415–e421

Abstract: Background: This study examined patterns of physical activity and associations with pain, function, fatigue, and sleep disturbance among individuals with knee or hip osteoarthritis.: Methods: Participants (n = 54) were enrolled in a telephone-based ... ...

Abstract	Background: This study examined patterns of physical activity and associations with pain, function, fatigue, and sleep disturbance among individuals with knee or hip osteoarthritis. Methods: Participants (n = 54) were enrolled in a telephone-based physical activity coaching intervention trial; all data were collected at baseline. Self-reported measures of pain and function (WOMAC [Western Ontario and McMaster Universities Osteoarthritis Index] subscales), fatigue (10-point numeric rating scale), and PROMIS (Patient-Reported Outcomes Information System) Sleep Disturbance were collected via telephone. Accelerometers were mailed to participants and were worn for at least 3 days. Proportion of time participants spent in sedentary behavior during the morning (from wake until 12:00 pm), afternoon (12:00 pm until 5:59 pm) and evening (6:00 pm until sleep) each day was averaged across all days of wear. Pearson correlations assessed associations between activity and self-reported measures. Results: Participants spent a large proportion of time in sedentary behavior: 65.6% of mornings, 70.0% of afternoons, and 76.6% of evenings. Associations between proportion of time spent in sedentary behavior and reported outcomes were generally strongest in the afternoon, strongest for WOMAC function, and lowest for PROMIS Sleep Disturbance. In the evening hours, sedentary time was most strongly associated with fatigue. Conclusions: Overall, findings stress the importance of reducing sedentary behavior among adults with osteoarthritis and suggest behavioral interventions may be strengthened by considering patients' within-day variation in symptoms and activity.
MeSH term(s)	Accelerometry ; Adult ; Exercise ; Humans ; Osteoarthritis, Hip/diagnosis ; Osteoarthritis, Knee/diagnosis ; Sedentary Behavior
Language	English
Publishing date	2021-04-28
Publishing country	United States
Document type	Clinical Trial ; Journal Article
ZDB-ID	1283266-2
ISSN	1536-7355 ; 1076-1608
ISSN (online)	1536-7355
ISSN	1076-1608
DOI	10.1097/RHU.0000000000001750
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