Background: The multifactorial heterogenous nature of chronic pain with its multiple comorbidities presents a formidable challenge in disentangling the aetiology underlying patient symptoms. Methods: Here, we performed genome-wide association studies (GWAS) of eight types of regional chronic pain using UK Biobank data (N=4,037-79,089 cases; N=239,125 controls), followed by bivariate linkage disequilibrium-score regression and latent causal variable analyses to determine (respectively) their genetic correlations and genetic causal proportion (GCP) parameters with 1,492 other complex traits. Findings: We report evidence of a shared genetic signature in common regional chronic pain types, with their genetic correlations and causal directions being broadly consistent across a wide array of biopsychosocial traits. Furthermore, we identified 5,942 significant genetic correlations, of which 570 trait pairs showed evidence of a likely causal association (|GCP| > 0.6; 5% false discovery rate), including 488 traits contributing to chronic pain while 82 were affected by pain. A range of somatic pathologies (e.g., musculoskeletal, visceral), psychiatric factors (e.g., depression, trauma, anxiety, mania, bipolar disorder), socioeconomic factors (e.g., occupation) and other medical comorbidities (e.g., cardiovascular disease) contributed to an increased risk of regional chronic pain. Conversely, each chronic pain type contributed to various other traits such as increased medication use (e.g., analgesics) and risk of ischaemic heart disease and depression. Interpretation: Findings of this data-driven study, through comprehensive analysis of a vast range of biopsychosocial factors, are indicative of a common genetic signature underlying eight regional chronic pain types. We identify a broad range of traits with genetic causal effects upon chronic pain, which may inform development of novel diagnostic and therapeutic strategies, as well as provide convergent support for various existing approaches.

A shared genetic signature for common chronic pain conditions and its impact on biopsychosocial traits

Chronic pain conditions are complex syndromes characterized by a mosaic of biological, psychological, and social factors. We derived predictive models for the number of co-existing pain sites in the UK Biobank and identified a common risk score that classified different chronic pain conditions in cross-sectional data, predicted the development of chronic pain in pain-free individuals, and determined the spreading of chronic pain to multiple sites or its recovery nine years later. The features with the strongest prognosis included sleeplessness, feeling 'fed-up', tiredness, stressful life events, and a BMI > 30. The risk score for pain was associated with an inflammatory blood marker, a polygenic risk score for pain, and a neuroimaging-based marker for sustained pain. The demonstration of a common biopsychosocial risk factor for different clinical pain conditions may help better characterize a general chronic pain syndrome, tailor research protocols, optimize patient randomization in clinical trials, and improve pain management.

A Data-Driven Biopsychosocial Framework Determining the Spreading of Chronic Pain

The mechanisms of chronic pain are complex, and genetic factors play an essential role in the development of chronic pain. Neuropathic pain (NP) and inflammatory pain (IP) are two primary components of chronic pain. Previous studies have uncovered some common biological processes in NP and IP. However, the shared genetic mechanisms remained poorly studied. We utilized multi-omics systematic analyses to investigate the shared genetic mechanisms of NP and IP. First, by integrating several genome-wide association studies (GWASs) with multi-omics data, we revealed the significant overlap of the gene co-expression modules in NP and IP. Further, we uncovered the shared biological pathways, including the previously reported mitochondrial electron transport and ATP metabolism, and stressed the role of genetic factors in chronic pain with neurodegenerative diseases. Second, we identified 24 conservative key drivers (KDs) contributing to NP and IP, containing two well-established pain genes, IL1B and OPRM1, and some novel potential pain genes, such as C5AR1 and SERPINE1. The subnetwork of those KDs highlighted the processes involving the immune system. Finally, gene expression analysis of the KDs in mouse models underlined two of the KDs, SLC6A15 and KCNQ5, with unidirectional regulatory functions in NP and IP. Our study provides strong evidence to support the current understanding of the shared genetic regulatory networks underlying NP and IP and potentially benefit the future common therapeutic avenues for chronic pain.

/pdf/shared-genetic-regulatory-networks-contribute-to-neuropathic-n2c9bxp0.pdf

Shared Genetic Regulatory Networks Contribute to Neuropathic and Inflammatory Pain: Multi-Omics Systems Analysis

Abstract Chronic pain is a common problem, with more than one-fifth of adult Americans reporting pain daily or on most days. It adversely affects quality of life and imposes substantial personal and economic costs. Efforts to treat chronic pain using opioids played a central role in precipitating the opioid crisis. Despite an estimated heritability of 25–50%, the genetic architecture of chronic pain is not well characterized, in part because studies have largely been limited to samples of European ancestry. To help address this knowledge gap, we conducted a cross-ancestry meta-analysis of pain intensity in 598,339 participants in the Million Veteran Program, which identified 125 independent genetic loci, 82 of which are novel. Pain intensity was genetically correlated with other pain phenotypes, level of substance use and substance use disorders, other psychiatric traits, education level, and cognitive traits. Integration of the GWAS findings with functional genomics data shows enrichment for putatively causal genes (n = 142) and proteins (n = 14) expressed in brain tissues, specifically in GABAergic neurons. Drug repurposing analysis identified anticonvulsants, beta-blockers, and calcium-channel blockers, among other drug groups, as having potential analgesic effects. Our results provide insights into key molecular contributors to the experience of pain and highlight attractive drug targets. 

/pdf/the-genetic-architecture-of-pain-intensity-in-a-sample-of-2n2w8b4x.pdf

The genetic architecture of pain intensity in a sample of 598,339 U.S. veterans

Chronic pain is a common problem, with more than one-fifth of adult Americans reporting pain daily or on most days. It adversely affects quality of life and imposes substantial personal and economic costs. Efforts to treat chronic pain using opioids played a central role in precipitating the opioid crisis. Despite an estimated heritability of 25-50%, the genetic architecture of chronic pain is not well characterized, in part because studies have largely been limited to samples of European ancestry. To help address this knowledge gap, we conducted a cross-ancestry meta-analysis of pain intensity in 598,339 participants in the Million Veteran Program, which identified 125 independent genetic loci, 82 of which are novel. Pain intensity was genetically correlated with other pain phenotypes, level of substance use and substance use disorders, other psychiatric traits, education level, and cognitive traits. Integration of the GWAS findings with functional genomics data shows enrichment for putatively causal genes (n = 142) and proteins (n = 14) expressed in brain tissues, specifically in GABAergic neurons. Drug repurposing analysis identified anticonvulsants, beta-blockers, and calcium-channel blockers, among other drug groups, as having potential analgesic effects. Our results provide insights into key molecular contributors to the experience of pain and highlight attractive drug targets.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10055465

Chronic pain is attributable to both local and systemic pathology. To investigate the latter, we focused on genetic risk shared among 24 chronic pain conditions in the UK Biobank. We conducted genome-wide association studies (GWAS) on all conditions and estimated genetic correlations among them, using these to model a factor structure in Genomic SEM. This revealed a general factor explaining most of the shared genetic variance in all conditions and an additional musculoskeletal pain-selective factor. Network analyses revealed a large cluster of highly genetically inter-connected conditions, with arthropathic, back, and neck pain showing the highest centrality. Functional annotation (FUMA) showed organogenesis, metabolism, transcription, and DNA repair as associated pathways, with enrichment for associated genes exclusively in brain tissues. Cross-reference with previous GWAS showed genetic overlap with cognition, mood, and brain structure. In sum, our results identify common genetic risks and suggest neurobiological and psychosocial mechanisms of vulnerability to chronic pain.

https://www.medrxiv.org/content/medrxiv/early/2022/06/30/2022.06.28.22277025.full.pdf

Identification and characterization of genetic risk shared across 24 chronic pain conditions in the UK Biobank.

Deficits in effective executive function, including inhibitory control are associated with risk for a number of psychiatric disorders and significantly impact everyday functioning. These complex traits have been proposed to serve as endophenotypes, however their genetic architecture is not yet well understood. To identify the common genetic variation associated with inhibitory control in the general population we performed the first trans-ancestry genome wide association study (GWAS) combining data across 8 sites and four ancestries (N=14,877) using behavioural traits derived from the stop-signal task, namely - go reaction time (GoRT), go reaction time variability (GoRT SD) and stop signal reaction time (SSRT). Although we did not identify genome wide significant associations for any of the three traits, GoRT SD and SSRT demonstrated significant and similar SNP heritability of 8.2%, indicative of an influence of genetic factors. Power analyses demonstrated that the number of common causal variants contributing to the heritability of these phenotypes is relatively high and larger sample sizes are necessary to robustly identify associations. The polygenic risk for ADHD was significantly associated with GoRT SD further supporting its suggested utility as an endophenotype for ADHD. Together these findings provide the first evidence indicating the influence of common genetic variation in the genetic architecture of inhibitory control quantified using objective behavioural traits derived from the stop-signal task.

/pdf/trans-ancestry-meta-analysis-of-genome-wide-association-28e3klcb.pdf

Trans-ancestry meta-analysis of genome wide association studies of inhibitory control

Autoimmune hepatitis (AIH) is a self-perpetuating inflammatory liver disease with significant morbidity and mortality risks. Patients undergo liver biopsy to confirm diagnosis and affirm subsequent remission. Advances in liquid biopsies show promise to replace tissue biopsy in cancer, however little research has been done in liver disease. Here, we use plasma chromatin immunoprecipitation and sequencing (cfChIP-seq) to analyze cell-free nucleosomes carrying an active histone modification which reports on gene transcription in the dying cells. Comparing plasma samples from pediatric AIH patients to a control group we identify immune-related transcriptional processes activated in hepatocytes of AIH patients. We devise a classifier that based on cfChIP-seq profiles distinguishes AIH from other conditions involving increased liver damage. Our work demonstrates the potential of plasma cfChIP-seq as a non-invasive diagnostic tool for AIH, which could replace the need for liver biopsy, aid accurate diagnoses, and enable further scientific exploration of AIH pathogenesis.

/pdf/identification-of-hepatocyte-immune-response-in-autoimmune-2z2v3z7y.pdf

N. Friedman

Papers

Identification and characterization of genetic risk shared across 24 chronic pain conditions in the UK Biobank.

Trans-ancestry meta-analysis of genome wide association studies of inhibitory control

Identification of hepatocyte immune response in Autoimmune Hepatitis from human plasma cfChIP-seq