---
title: "Multi-organ imaging genetics: integrating brain–body links for neurological disease"
id: "nature-reviews-neurology-0-multi-organ-imaging-genetics-towards-an-integrated-view-of-brain-body-and-brain"
canonical_url: "https://medichelpline.com/clinical-feed/nature-reviews-neurology-0-multi-organ-imaging-genetics-towards-an-integrated-view-of-brain-body-and-brain"
content_type: "clinical_feed_article"
specialty: "Neurology"
source_name: "Nature Reviews Neurology"
source_url: "https://www.nature.com/articles/s41582-026-01276-x"
published_at: "2026-10-19T12:00:00.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Multi-organ imaging genetics: integrating brain–body links for neurological disease
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/nature-reviews-neurology-0-multi-organ-imaging-genetics-towards-an-integrated-view-of-brain-body-and-brain
- **Specialty:** [Neurology](https://medichelpline.com/clinical-feed/neurology.md)
- **Primary Source:** Nature Reviews Neurology
- **Source URL:** [Original Journal Publication](https://www.nature.com/articles/s41582-026-01276-x)
- **Published At:** 2026-10-19T12:00:00.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- Population cohorts that combine genomics with whole-body, multimodal imaging enable discovery of genetic determinants of brain structure and function in a bodily context. - Historically, imaging genetics targeted single organs; the authors reported a shift toward a **brain–body** perspective that integrates heart, retina, liver, skeleton and other organ imaging with brain measures. - Large studies cited include UK Biobank-based genome-wide association work on brain imaging and white matter microstructure, plus cardiac–brain and eye–brain imaging genetics papers that reveal shared loci and correlated phenotypes. - The review outlines evidence for shared genomic loci, colocalized causal variants and Mendelian randomization links between body imaging phenotypes and major neurological disorders such as **Alzheimer disease**, **stroke** and **schizophrenia**. - Investigators proposed a three-step analytical pipeline: nominate causal genes, assemble organ-enriched network modules and perform cross-field validation to move from statistical association toward mechanistic inference. - Data resources and large-scale multimodal imaging cohorts are summarized (figures illustrated data architecture and analytical workflows). - The authors argue that clinical translation is already shifting to account for multi-organ interactions and multimorbidity, and they reference emerging clinical practice guidance on brain–heart multimorbidity. - A roadmap is presented for embedding **agentic AI** as collaborative co-scientists to speed cross-disciplinary discovery and act as infrastructure for the field. - The previewed article indicates further detail in the full text; the source did not report experimental parameters, detailed methods or new primary data within the previewed content.
## Clinical Analysis & Structured Key Points
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[nature](https://www.nature.com/) 2. [nature reviews neurology](https://www.nature.com/nrneurol) 3. [roadmaps](https://www.nature.com/nrneurol/articles?type=roadmap) 4. article * Roadmap * Published: 19 October 2026 # Multi-organ imaging genetics: towards an integrated view of brain, body and brain diseases * [Zirui Fan](https://www.nature.com/articles/s41582-026-01276-x#auth-Zirui-Fan-Aff1)[1](https://www.nature.com/articles/s41582-026-01276-x#Aff1) & * [Bingxin Zhao](https://www.nature.com/articles/s41582-026-01276-x#auth-Bingxin-Zhao-Aff1-Aff2) [ORCID: orcid.org/0000-0002-0979-7891](https://orcid.org/0000-0002-0979-7891)[1](https://www.nature.com/articles/s41582-026-01276-x#Aff1),[2](https://www.nature.com/articles/s41582-026-01276-x#Aff2) [_Nature Reviews Neurology_](https://www.nature.com/nrneurol) (2026) [Cite this article](https://www.nature.com/articles/s41582-026-01276-x#citeas) Save article [ View saved research ](https://www.nature.com/saved-research) ## Abstract Population-based cohorts that combine genetic data with whole-body multimodal imaging are transforming how we map the genetic architecture of the brain in its broader bodily context. Historically, imaging genetics has focused largely on single organs, especially the brain, with separate efforts targeting the heart, skeleton and other organs for systemic diseases, and limited integration across organ systems. Yet, strong brain–body interactions and the high multimorbidity of brain and systemic diseases highlight the need for a brain-centred multi-organ perspective. Here we introduce the emerging field of brain-focused multi-organ imaging genetics, outlining key data resources and interdisciplinary analytical frameworks for large-scale multi-organ genetic discovery and reviewing the genetic associations between brain diseases and imaging phenotypes across organ systems. We discuss how these advances support a whole-body integrated view of brain health and disease and how they are beginning to reshape clinical translation for neurological conditions. We outline a roadmap for agentic artificial intelligence co-scientists that work alongside human researchers throughout the scientific discovery process, arguing that such systems will be essential for achieving an integrated understanding of brain health and disease, both as tools for individual researchers and as a collaborative infrastructure for the whole field. ## Key points * Large-scale cohorts combining genetic data with multi-organ imaging are enabling brain-focused genetic discovery across organ systems at scale and breadth. * The genetic determinants of brain disorders are deeply intertwined with imaging phenotypes across the heart, retina and other organs, revealing a distributed whole-body genetic architecture underlying neurological and neuropsychiatric conditions. * Multi-organ imaging genetics has uncovered shared genomic loci, colocalized causal variants and Mendelian randomization-supported genetic connections between body imaging phenotypes and major brain disorders such as Alzheimer disease, stroke and schizophrenia. * A three-step analytical approach, from causal gene nomination through organ-enriched network modules to cross-field validation, provides a principled framework for moving beyond statistical genetic association towards mechanistic understanding of brain disorders. * Brain–body imaging genetics and broader multi-organ interaction findings are beginning to reshape clinical translation and clinical care beyond organ boundaries. * Agentic AI co-scientists capable of empowering cross-disciplinary scientific discovery will be essential for realizing an integrated, whole-body understanding of brain health and disease. This is a preview of subscription content, [access via your institution](https://wayf.springernature.com?redirect_uri=https%3A%2F%2Fwww.nature.com%2Farticles%2Fs41582-026-01276-x) ## Access options [ Access through your institution ](https://wayf.springernature.com?redirect_uri=https%3A%2F%2Fwww.nature.com%2Farticles%2Fs41582-026-01276-x) Access Nature and 54 other Nature Portfolio journals Get Nature+, our best-value online-access subscription 27,99 € / 30 days cancel any time [Learn more](https://shop.nature.com/products/plus/?region=ROW) Subscribe to this journal Receive 12 print issues and online access 176,64 € per year only 14,72 € per issue [Learn more](https://www.nature.com/nrneurol/subscribe) Buy this article * Purchase on SpringerLink * Instant access to the full article PDF. 39,95 € Prices may be subject to local taxes which are calculated during checkout ### Additional access options: * [Log in](https://idp.nature.com/auth/personal/springernature?client_id=grover&redirect_uri=https%3A%2F%2Fwww.nature.com%2Farticles%2Fs41582-026-01276-x) * [Learn about institutional subscriptions](https://www.springernature.com/gp/librarians/licensing/license-options) * [Read our FAQs](https://support.nature.com/en/support/home) * [Contact customer support](https://www.springernature.com/gp/contact) **Fig. 1: Interconnected components of brain-focused multi-organ imaging genetics.** ![](https://media.springernature.com/m312/springer-static/image/art%3A10.1038%2Fs41582-026-01276-x/MediaObjects/41582_2026_1276_Fig1_HTML.png) **Fig. 2: Data resources for brain-focused multi-organ imaging genetics.** ![](https://media.springernature.com/m312/springer-static/image/art%3A10.1038%2Fs41582-026-01276-x/MediaObjects/41582_2026_1276_Fig2_HTML.png) **Fig. 3: Analytical pipeline for multi-organ imaging genetics.** ![](https://media.springernature.com/m312/springer-static/image/art%3A10.1038%2Fs41582-026-01276-x/MediaObjects/41582_2026_1276_Fig3_HTML.png) **Fig. 4: Agentic AI enabling human–AI collaboration in multi-organ imaging genetics discovery.** ![](https://media.springernature.com/m312/springer-static/image/art%3A10.1038%2Fs41582-026-01276-x/MediaObjects/41582_2026_1276_Fig4_HTML.png) ### Explore related subjects Discover the latest articles and news in related subjects. * [Biomarkers](https://www.nature.com/subjects/biomarkers) * [Neurological disorders](https://www.nature.com/subjects/neurological-disorders) * [Neuroscience](https://www.nature.com/subjects/neuroscience) ## References 1. 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