Matt Fillingim
@FillingimMatt
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@McGillu Neuroscience PhD Candidate studying #ChronicPain #Biomarkers #Neuroimaging
Montréal, Québec
Joined December 2011
Thrilled to share our new paper in @NatureHumBehav!. We show that combining biological 🧬 and psychosocial 📋 data offers a much stronger, more reliable path to predicting pain and diagnosis. 🧵
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RT @cremieuxrecueil: Phenotyping is the vast, minimally-explored frontier in genome-wide association studies. Important thread🧵. Briefly,….
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RT @misicbata: Benchmarking methods for mapping functional connectivity in the brain | What is the best FC metric?….
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RT @torwager: Beautiful paper on #biomarkers, #neuromarkers, and psychosocial predictors of chronic pain and associated #chronicdiseases. A….
nature.com
Nature Human Behaviour - Fillingim et al. show that biological and psychosocial factors jointly predict conditions associated with chronic pain.
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RT @DrZoffness: 🔥Most important paper of 2025🔥.👉Injury/disease don't reliably predict pain.👉Biomarkers alone can't explain pain.👉PSYCHOSOCI….
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Excited to share our new publication! See the thread and article below 👇.
Thrilled to share our new paper in @NatureHumBehav!. We show that combining biological 🧬 and psychosocial 📋 data offers a much stronger, more reliable path to predicting pain and diagnosis. 🧵
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RT @aecrpain: another Nature (this time @NatureHumBehav) paper from the @evp82 lab, this time from @FillingimMatt.
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RT @GVG_Neuro: Great paper demonstrating how taking into account the social context of your participants can improve your understanding and….
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RT @evp82: Our new @NatureHumBehav paper shows why we need a holistic pain biomarker framework. ML on blood tests, brain/bone imaging & gen….
nature.com
Nature Human Behaviour - Fillingim et al. show that biological and psychosocial factors jointly predict conditions associated with chronic pain.
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RT @NatureHumBehav: Fillingim et al. show that biological and psychosocial factors jointly predict chronic pain associated conditions.https….
nature.com
Nature Human Behaviour - Fillingim et al. show that biological and psychosocial factors jointly predict conditions associated with chronic pain.
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Huge thanks to our incredible team and collaborators. Read the full paper here: Grateful to @NatureHumBehav for publishing this work. #ChronicPain #PrecisionMedicine #Biomarkers #Psychosocial #MachineLearning.
nature.com
Nature Human Behaviour - Fillingim et al. show that biological and psychosocial factors jointly predict conditions associated with chronic pain.
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Adding psychosocial context dramatically improved prediction accuracy across all pain phenotypes. 🧬 + 📋 = 🔍. This synergy paints a richer picture of pain vulnerability and brings us closer to personalized pain care.
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We created biomarker and psychosocial risk scores and grouped participants into quintiles. Those high on both risks had over 2× higher incidence of painful conditions over 15 years, while those high on just one showed little to no added risk.
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Biomarkers alone accurately predicted many painful medical conditions, often outperforming psychosocial models. But for self-reported pain, biology wasn’t enough, psychosocial models performed significantly better.
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We then compared the biological models to psychosocial models spanning mental health, physical well-being, and sociodemographic factors.
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We applied machine learning to four biological data types:🩸blood assays, 🦴bone scans, 🧠brain imaging, and 🧬genetics, to develop biomarkers for conditions like arthritis or migraine, as well as self-reported bodily pain.
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We asked: Can combining biological and psychosocial information improve prediction of chronic pain conditions?. Spoiler: Yes, significantly.
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