Polyconnectomic Scoring of Functional Connectivity Patterns Across Eight Neuropsychiatric and Three Neurodegenerative Disorders

Ilan Libedinsky; Koen Helwegen; Jackson Boonstra; Laura Guerrero Simón; Marius Gruber; Jonathan Repple; Tilo Kircher; Udo Dannlowski; Martijn P van den Heuvel

doi:10.1016/j.biopsych.2024.10.007

Polyconnectomic Scoring of Functional Connectivity Patterns Across Eight Neuropsychiatric and Three Neurodegenerative Disorders

Ilan Libedinsky, Koen Helwegen, Jackson Boonstra, Laura Guerrero Simón, Marius Gruber, Jonathan Repple, Tilo Kircher, Udo Dannlowski, Martijn P van den Heuvel

Research output: Contribution to Journal › Article › Academic › peer-review

Abstract

BACKGROUND: Neuropsychiatric and neurodegenerative disorders involve diverse changes in brain functional connectivity. As an alternative to approaches that search for specific mosaic patterns of affected connections and networks, we used polyconnectomic scoring to quantify disorder-related whole-brain connectivity signatures into interpretable, personalized scores.

METHODS: The polyconnectomic score (PCS) measures the extent to which an individual's functional connectivity mirrors the whole-brain circuitry characteristics of a trait. We computed PCSs for 8 neuropsychiatric conditions (attention-deficit/hyperactivity disorder, anxiety-related disorders, autism spectrum disorder, obsessive-compulsive disorder, bipolar disorder, major depressive disorder, schizoaffective disorder, and schizophrenia) and 3 neurodegenerative conditions (Alzheimer's disease, frontotemporal dementia, and Parkinson's disease) across 22 datasets with resting-state functional magnetic resonance imaging data from 10,667 individuals (5325 patients, 5342 control participants). We also examined PCSs in 26,673 individuals from the population-based UK Biobank cohort.

RESULTS: PCSs were consistently higher in out-of-sample patients across 6 of the 8 neuropsychiatric and across all 3 investigated neurodegenerative disorders ([minimum, maximum]: area under the receiver operating characteristic curve = [0.55, 0.73], false discovery rate-corrected p [pFDR] = [1.8 × 10-16, 4.5 × 10-2]). Individuals with elevated PCS levels for neuropsychiatric conditions exhibited higher neuroticism (pFDR < 9.7 × 10-5), lower cognitive performance (pFDR < 5.3 × 10-5), and lower general well-being (pFDR < 9.7 × 10-4).

CONCLUSIONS: Our findings reveal generalizable whole-brain connectivity alterations in brain disorders. Polyconnectomic scoring effectively aggregates disorder-related signatures across the entire brain into an interpretable, participant-specific metric. A toolbox is provided for PCS computation.

Original language	English
Pages (from-to)	1045-1058
Number of pages	14
Journal	Biological psychiatry
Volume	97
Issue number	11
Early online date	16 Oct 2024
DOIs	https://doi.org/10.1016/j.biopsych.2024.10.007
Publication status	Published - 1 Jun 2025

Bibliographical note

Funding

Data collection and sharing for this project was funded by the ADNI (Alzheimer\u2019s Disease Neuroimaging Initiative) (NIH Grant No. U01 AG024904) and Department of Defense ADNI (Department of Defense award No. W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie; Alzheimer\u2019s Association; Alzheimer\u2019s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd. and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health ( http://www.fnih.org ). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer\u2019s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuroimaging at the University of Southern California. Analyses were carried out on the Genetic Cluster Computer hosted by the Dutch National computing and Networking Services SURFsara and financed by the Netherlands Organization for Scientific Research (NWO: 480-05-003), the VU University (Amsterdam, the Netherlands), and the Dutch Brain Foundation. The Healthy Brain Network is supported by philanthropic contributions from the following individuals, foundations, and organizations: Margaret Bilotti; Brooklyn Nets; Agapi and Bruce Burkard; James Chang; Phyllis Green and Randolph Cowen; Grieve Family Fund; Susan Miller and Byron Grote; Sarah and Geoff Gund; George Hall; Jonathan M. Harris Family Foundation; Joseph P. Healey; the Hearst Foundations; Eve and Ross Jaffe; Howard & Irene Levine Family Foundation; Rachael and Marshall Levine; George and Nitzia Logothetis; Christine and Richard Mack; Julie Minskoff; Valerie Mnuchin; Morgan Stanley Foundation; Amy and John Phelan; Roberts Family Foundation; Jim and Linda Robinson Foundation, Inc.; Linda and Richard Schaps; Zibby Schwarzman; Abigail Pogrebin and David Shapiro; Stavros Niarchos Foundation; Preethi Krishna and Ram Sundaram; Amy and John Weinberg; donors to the 2013 Child Advocacy Award Dinner Auction; and donors to the 2012 Brant Art Auction. Data collection and sharing for this project was funded by the NIFD (Frontotemporal Lobar Degeneration Neuroimaging Initiative) (NIH Grant No. R01 AG032306). The study is coordinated through the University of California, San Francisco Memory and Aging Center. NIFD data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. The FOR 2107 cohort was funded by the German Research Foundation (Grant Nos. FOR2107 KI588/14-1, KI588/14-2, KI588/20-1, and KI588/22-1 [to TK]; DA1151/5-1, DA1151/5-2, DA1151/9-1, DA1151/10-1, and DA1151/11-1 [to UD]; and SFB-TRR393 [to TK and UD]) and the Interdisciplinary Center for Clinical Research of the medical faculty of M\u00FCnster (Grant No. Dan3/022/22 [to UD]). Biosamples and corresponding data were sampled, processed, and stored in the Marburg Biobank CBBMR. This study was funded by the ERC Consolidator grant from the European Research Council (Grant No. 101001062 CONNECT [to MPvdH]). Data collection and sharing for Japanese Strategic Research Program for the Promotion of Brain Science (SRPBS) was provided by the DecNef Department at the Advanced Telecommunication Research Institute International, Kyoto, Kyoto Prefecture, Japan. This work was supported by the Japan Agency for Medical Research and Development (Grant Nos. JP17dm0107044, JP20dm0307004, JP20dm0307008, JP20dm0307002, and JP20dm0307009). Center of Biomedical Research Excellence (COBRE) data were downloaded from the Collaborative Informatics and Neuroimaging Suite Data Exchange tool ( http://coins.mrn.org/dx ), and data collection was performed at the Mind Research Network and funded by COBRE (Grant No. 5P20RR021938/P20GM103472 [to V. Calhoun]) from the National Institutes of Health (NIH). Data were provided (in part) by Open Access Series of Imaging Studies (OASIS) (T. Benzinger, D. Marcus, J. Morris; NIH Grant Nos. P50 AG00561, P30 NS09857781, P01 AG026276, P01 AG003991, R01 AG043434, UL1 TR000448, and R01 EB009352). AV-45 doses were provided by Avid Radiopharmaceuticals, a wholly owned subsidiary of Eli Lilly. We acknowledge the contribution of data made available through SchizConnect ( http://schizconnect.org ; funded by NIMH Grant No. 1U01 MH097435), NDA ( https://nda.nih.gov ), OpenNeuro ( http://openneuro.org ), and XNAT Central ( http://central.xnat.org ).

Funders	Funder number
Euroimmun
Dutch National computing and Networking Services SURFsara
National Institute of Biomedical Imaging and Bioengineering
Hearst Foundations
Eli Lilly and Company
Department of Defense ADNI
Vrije Universiteit Amsterdam
Roberts Family Foundation
Dutch Brain Foundation
John Phelan
Alzheimer's Disease Neuroimaging Initiative
NIFD
Roche Canada
National Institute on Aging
Nederlandse Organisatie voor Wetenschappelijk Onderzoek	480-05-003
Deutsche Forschungsgemeinschaft	DA1151/9-1, DA1151/5-2, DA1151/10-1, DA1151/5-1, DA1151/11-1, FOR2107 KI588/14-1, KI588/20-1, SFB-TRR393, KI588/22-1, KI588/14-2
U.S. Department of Defense	W81XWH-12-2-0012
European Research Council	101001062
National Institutes of Health	R01 AG043434, R01 AG032306, R01 EB009352, U01 AG024904, P30 NS09857781, P01 AG026276, P50 AG00561, UL1 TR000448, P01 AG003991
Japan Agency for Medical Research and Development	JP17dm0107044, JP20dm0307004, JP20dm0307002, JP20dm0307009, JP20dm0307008
COBRE	5P20RR021938/P20GM103472
Interdisciplinary Center for Clinical Research of the medical faculty of Münster	Dan3/022/22
National Institute of Mental Health	1U01 MH097435

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10.1016/j.biopsych.2024.10.007

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@article{f77550163c11413387f070c5926ba2b5,

title = "Polyconnectomic Scoring of Functional Connectivity Patterns Across Eight Neuropsychiatric and Three Neurodegenerative Disorders",

abstract = "BACKGROUND: Neuropsychiatric and neurodegenerative disorders involve diverse changes in brain functional connectivity. As an alternative to approaches that search for specific mosaic patterns of affected connections and networks, we used polyconnectomic scoring to quantify disorder-related whole-brain connectivity signatures into interpretable, personalized scores.METHODS: The polyconnectomic score (PCS) measures the extent to which an individual's functional connectivity mirrors the whole-brain circuitry characteristics of a trait. We computed PCSs for 8 neuropsychiatric conditions (attention-deficit/hyperactivity disorder, anxiety-related disorders, autism spectrum disorder, obsessive-compulsive disorder, bipolar disorder, major depressive disorder, schizoaffective disorder, and schizophrenia) and 3 neurodegenerative conditions (Alzheimer's disease, frontotemporal dementia, and Parkinson's disease) across 22 datasets with resting-state functional magnetic resonance imaging data from 10,667 individuals (5325 patients, 5342 control participants). We also examined PCSs in 26,673 individuals from the population-based UK Biobank cohort.RESULTS: PCSs were consistently higher in out-of-sample patients across 6 of the 8 neuropsychiatric and across all 3 investigated neurodegenerative disorders ([minimum, maximum]: area under the receiver operating characteristic curve = [0.55, 0.73], false discovery rate-corrected p [pFDR] = [1.8 × 10-16, 4.5 × 10-2]). Individuals with elevated PCS levels for neuropsychiatric conditions exhibited higher neuroticism (pFDR < 9.7 × 10-5), lower cognitive performance (pFDR < 5.3 × 10-5), and lower general well-being (pFDR < 9.7 × 10-4).CONCLUSIONS: Our findings reveal generalizable whole-brain connectivity alterations in brain disorders. Polyconnectomic scoring effectively aggregates disorder-related signatures across the entire brain into an interpretable, participant-specific metric. A toolbox is provided for PCS computation.",

author = "Ilan Libedinsky and Koen Helwegen and Jackson Boonstra and Sim{\'o}n, \{Laura Guerrero\} and Marius Gruber and Jonathan Repple and Tilo Kircher and Udo Dannlowski and \{van den Heuvel\}, \{Martijn P\}",

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doi = "10.1016/j.biopsych.2024.10.007",

language = "English",

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T1 - Polyconnectomic Scoring of Functional Connectivity Patterns Across Eight Neuropsychiatric and Three Neurodegenerative Disorders

AU - Libedinsky, Ilan

AU - Helwegen, Koen

AU - Boonstra, Jackson

AU - Simón, Laura Guerrero

AU - Gruber, Marius

AU - Repple, Jonathan

AU - Kircher, Tilo

AU - Dannlowski, Udo

AU - van den Heuvel, Martijn P

PY - 2025/6/1

Y1 - 2025/6/1

N2 - BACKGROUND: Neuropsychiatric and neurodegenerative disorders involve diverse changes in brain functional connectivity. As an alternative to approaches that search for specific mosaic patterns of affected connections and networks, we used polyconnectomic scoring to quantify disorder-related whole-brain connectivity signatures into interpretable, personalized scores.METHODS: The polyconnectomic score (PCS) measures the extent to which an individual's functional connectivity mirrors the whole-brain circuitry characteristics of a trait. We computed PCSs for 8 neuropsychiatric conditions (attention-deficit/hyperactivity disorder, anxiety-related disorders, autism spectrum disorder, obsessive-compulsive disorder, bipolar disorder, major depressive disorder, schizoaffective disorder, and schizophrenia) and 3 neurodegenerative conditions (Alzheimer's disease, frontotemporal dementia, and Parkinson's disease) across 22 datasets with resting-state functional magnetic resonance imaging data from 10,667 individuals (5325 patients, 5342 control participants). We also examined PCSs in 26,673 individuals from the population-based UK Biobank cohort.RESULTS: PCSs were consistently higher in out-of-sample patients across 6 of the 8 neuropsychiatric and across all 3 investigated neurodegenerative disorders ([minimum, maximum]: area under the receiver operating characteristic curve = [0.55, 0.73], false discovery rate-corrected p [pFDR] = [1.8 × 10-16, 4.5 × 10-2]). Individuals with elevated PCS levels for neuropsychiatric conditions exhibited higher neuroticism (pFDR < 9.7 × 10-5), lower cognitive performance (pFDR < 5.3 × 10-5), and lower general well-being (pFDR < 9.7 × 10-4).CONCLUSIONS: Our findings reveal generalizable whole-brain connectivity alterations in brain disorders. Polyconnectomic scoring effectively aggregates disorder-related signatures across the entire brain into an interpretable, participant-specific metric. A toolbox is provided for PCS computation.

AB - BACKGROUND: Neuropsychiatric and neurodegenerative disorders involve diverse changes in brain functional connectivity. As an alternative to approaches that search for specific mosaic patterns of affected connections and networks, we used polyconnectomic scoring to quantify disorder-related whole-brain connectivity signatures into interpretable, personalized scores.METHODS: The polyconnectomic score (PCS) measures the extent to which an individual's functional connectivity mirrors the whole-brain circuitry characteristics of a trait. We computed PCSs for 8 neuropsychiatric conditions (attention-deficit/hyperactivity disorder, anxiety-related disorders, autism spectrum disorder, obsessive-compulsive disorder, bipolar disorder, major depressive disorder, schizoaffective disorder, and schizophrenia) and 3 neurodegenerative conditions (Alzheimer's disease, frontotemporal dementia, and Parkinson's disease) across 22 datasets with resting-state functional magnetic resonance imaging data from 10,667 individuals (5325 patients, 5342 control participants). We also examined PCSs in 26,673 individuals from the population-based UK Biobank cohort.RESULTS: PCSs were consistently higher in out-of-sample patients across 6 of the 8 neuropsychiatric and across all 3 investigated neurodegenerative disorders ([minimum, maximum]: area under the receiver operating characteristic curve = [0.55, 0.73], false discovery rate-corrected p [pFDR] = [1.8 × 10-16, 4.5 × 10-2]). Individuals with elevated PCS levels for neuropsychiatric conditions exhibited higher neuroticism (pFDR < 9.7 × 10-5), lower cognitive performance (pFDR < 5.3 × 10-5), and lower general well-being (pFDR < 9.7 × 10-4).CONCLUSIONS: Our findings reveal generalizable whole-brain connectivity alterations in brain disorders. Polyconnectomic scoring effectively aggregates disorder-related signatures across the entire brain into an interpretable, participant-specific metric. A toolbox is provided for PCS computation.

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DO - 10.1016/j.biopsych.2024.10.007

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Polyconnectomic Scoring of Functional Connectivity Patterns Across Eight Neuropsychiatric and Three Neurodegenerative Disorders

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