Seth N Levin1, Claire S Riley1, Amar Dhand1, Charles C White1, Shruthi Venkatesh1, Blake Boehm1, Caren Nassif1, Lauren Socia1, Kaho Onomichi1, Victoria M Leavitt1, Libby Levine1, Rock Heyman1, Rebecca S Farber1, Wendy S Vargas1, Zongqi Xia1, Philip L De Jager2. 1. From the Multiple Sclerosis Center and the Center for Translational & Computational Neuroimmunology, Department of Neurology (S.N.L., C.S.R., C.N., L.S., K.O., V.M.L., L.L., R.S.F., W.S.V., P.L.D.J.), and The Taub Institute for Alzheimer's Disease Research (P.L.D.J.), Columbia University Irving Medical Center, New York, NY; Department of Neurology (A.D.), Brigham and Women's Hospital, Harvard Medical School; Network Science Institute (A.D.), Northeastern University, Boston; Broad Institute (C.C.W., Z.X., P.L.D.J.), Cell Circuits Program, Cambridge, MA; and Department of Neurology (S.V., B.B., R.H., Z.X.), University of Pittsburgh, PA. 2. From the Multiple Sclerosis Center and the Center for Translational & Computational Neuroimmunology, Department of Neurology (S.N.L., C.S.R., C.N., L.S., K.O., V.M.L., L.L., R.S.F., W.S.V., P.L.D.J.), and The Taub Institute for Alzheimer's Disease Research (P.L.D.J.), Columbia University Irving Medical Center, New York, NY; Department of Neurology (A.D.), Brigham and Women's Hospital, Harvard Medical School; Network Science Institute (A.D.), Northeastern University, Boston; Broad Institute (C.C.W., Z.X., P.L.D.J.), Cell Circuits Program, Cambridge, MA; and Department of Neurology (S.V., B.B., R.H., Z.X.), University of Pittsburgh, PA. pld2115@cumc.columbia.edu.
Abstract
OBJECTIVE: To test the association between physical function and the social environment in multiple sclerosis (MS), we quantified personal social networks. METHODS: In this cross-sectional study, we analyzed data from 2 academic MS centers, with center 1 serving as a discovery group and center 2 as the extension group. We performed a meta-analysis of the centers to extend the analysis. We used responses from a questionnaire to map the structure and health habits of participants' social networks as well as the NIH Patient-Reported Outcomes Measurement Information System (PROMIS) physical function scale (0-100, mean 50 for US general population) as the primary outcome. We applied multivariable models to test the association between network metrics and physical function. RESULTS: The discovery cohort included 263 patients with MS: 81% were women, 96% non-Hispanic European, 78% had relapsing MS, average age was 50 (12.4) years, and mean disease duration was 17 (12.3) years. The extension group included 163 patients, who were younger, more racially diverse, and less physically disabled, and had shorter disease duration. In the meta-analysis, higher network constraint, a measure of tightly bound networks, was associated with worse physical function (β = -0.163 ± 0.047, p < 0.001), while larger network effective size, a measure of clustered groups in the network, correlated with better physical function (β = 0.134 ± 0.046, p = 0.003). CONCLUSIONS: Our study highlights personal networks as an important environmental factor associated with physical function in MS. Patients with close-knit networks had worse function than those with more open networks. Longitudinal studies are warranted to evaluate a causal relationship between network structure and physical impairment.
OBJECTIVE: To test the association between physical function and the social environment in multiple sclerosis (MS), we quantified personal social networks. METHODS: In this cross-sectional study, we analyzed data from 2 academic MS centers, with center 1 serving as a discovery group and center 2 as the extension group. We performed a meta-analysis of the centers to extend the analysis. We used responses from a questionnaire to map the structure and health habits of participants' social networks as well as the NIH Patient-Reported Outcomes Measurement Information System (PROMIS) physical function scale (0-100, mean 50 for US general population) as the primary outcome. We applied multivariable models to test the association between network metrics and physical function. RESULTS: The discovery cohort included 263 patients with MS: 81% were women, 96% non-Hispanic European, 78% had relapsing MS, average age was 50 (12.4) years, and mean disease duration was 17 (12.3) years. The extension group included 163 patients, who were younger, more racially diverse, and less physically disabled, and had shorter disease duration. In the meta-analysis, higher network constraint, a measure of tightly bound networks, was associated with worse physical function (β = -0.163 ± 0.047, p < 0.001), while larger network effective size, a measure of clustered groups in the network, correlated with better physical function (β = 0.134 ± 0.046, p = 0.003). CONCLUSIONS: Our study highlights personal networks as an important environmental factor associated with physical function in MS. Patients with close-knit networks had worse function than those with more open networks. Longitudinal studies are warranted to evaluate a causal relationship between network structure and physical impairment.
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