A family-based study to identify genetic biomarkers of fibromyalgia: consideration of patients' subgroups
Evidence from genome-wide and candidate gene association studies, familial aggregation and linkage analyses demonstrate the genetic contribution to fibromyalgia (FM) disease. This study aimed to identify genetic biomarkers of FM and its related comorbid disorders, by exploring 41 polymorphisms poten...
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| Veröffentlicht in: | Clinical and experimental rheumatology Jg. 39 Suppl 130; H. 3; S. 144 |
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| Hauptverfasser: | , , , , , , , , , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
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01.01.2021
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| ISSN: | 0392-856X |
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| Abstract | Evidence from genome-wide and candidate gene association studies, familial aggregation and linkage analyses demonstrate the genetic contribution to fibromyalgia (FM) disease. This study aimed to identify genetic biomarkers of FM and its related comorbid disorders, by exploring 41 polymorphisms potentially involved in FM pathogenesis in families with at least one patient with FM.OBJECTIVESEvidence from genome-wide and candidate gene association studies, familial aggregation and linkage analyses demonstrate the genetic contribution to fibromyalgia (FM) disease. This study aimed to identify genetic biomarkers of FM and its related comorbid disorders, by exploring 41 polymorphisms potentially involved in FM pathogenesis in families with at least one patient with FM.Core symptoms were assessed, and blood samples collected from 556 patients with FM and 395 healthy relatives. For the genetic study, a final sample of 401 FM patients and 232 healthy controls was selected, discarding patients with concomitant pathologies and controls with chronic pain. A family-based approach using DFAM test (Plink) and SNPs (single nucleotide polymorphisms) combination analyses to compare FM patients vs. controls were first applied. Second, the genotypic distribution of subgroups of FM patients, stratified by severe vs. mild symptoms of pain, depression and sleep impairment, was considered.METHODSCore symptoms were assessed, and blood samples collected from 556 patients with FM and 395 healthy relatives. For the genetic study, a final sample of 401 FM patients and 232 healthy controls was selected, discarding patients with concomitant pathologies and controls with chronic pain. A family-based approach using DFAM test (Plink) and SNPs (single nucleotide polymorphisms) combination analyses to compare FM patients vs. controls were first applied. Second, the genotypic distribution of subgroups of FM patients, stratified by severe vs. mild symptoms of pain, depression and sleep impairment, was considered.No evidence of associations with FM per se were detected, using either a family-based approach or SNPs combination analyses. However, considering the subgroups of FM patients, the SNP rs6454674 (CNR1, cannabinoid receptor 1 gene) was found as a potential genetic marker of FM correlated with depression (p<.001).RESULTSNo evidence of associations with FM per se were detected, using either a family-based approach or SNPs combination analyses. However, considering the subgroups of FM patients, the SNP rs6454674 (CNR1, cannabinoid receptor 1 gene) was found as a potential genetic marker of FM correlated with depression (p<.001).No significant associations using either the family-based analysis or the SNPs combination tests dissociated FM patients and their healthy relatives. FM patients with and without depression showed a significant difference in the genotypic distribution related to the SNP rs6454674 in the cannabinoid receptor 1 gene (CNR1) indicating that FM is not a homogenous disorder.CONCLUSIONSNo significant associations using either the family-based analysis or the SNPs combination tests dissociated FM patients and their healthy relatives. FM patients with and without depression showed a significant difference in the genotypic distribution related to the SNP rs6454674 in the cannabinoid receptor 1 gene (CNR1) indicating that FM is not a homogenous disorder. |
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| AbstractList | Evidence from genome-wide and candidate gene association studies, familial aggregation and linkage analyses demonstrate the genetic contribution to fibromyalgia (FM) disease. This study aimed to identify genetic biomarkers of FM and its related comorbid disorders, by exploring 41 polymorphisms potentially involved in FM pathogenesis in families with at least one patient with FM.OBJECTIVESEvidence from genome-wide and candidate gene association studies, familial aggregation and linkage analyses demonstrate the genetic contribution to fibromyalgia (FM) disease. This study aimed to identify genetic biomarkers of FM and its related comorbid disorders, by exploring 41 polymorphisms potentially involved in FM pathogenesis in families with at least one patient with FM.Core symptoms were assessed, and blood samples collected from 556 patients with FM and 395 healthy relatives. For the genetic study, a final sample of 401 FM patients and 232 healthy controls was selected, discarding patients with concomitant pathologies and controls with chronic pain. A family-based approach using DFAM test (Plink) and SNPs (single nucleotide polymorphisms) combination analyses to compare FM patients vs. controls were first applied. Second, the genotypic distribution of subgroups of FM patients, stratified by severe vs. mild symptoms of pain, depression and sleep impairment, was considered.METHODSCore symptoms were assessed, and blood samples collected from 556 patients with FM and 395 healthy relatives. For the genetic study, a final sample of 401 FM patients and 232 healthy controls was selected, discarding patients with concomitant pathologies and controls with chronic pain. A family-based approach using DFAM test (Plink) and SNPs (single nucleotide polymorphisms) combination analyses to compare FM patients vs. controls were first applied. Second, the genotypic distribution of subgroups of FM patients, stratified by severe vs. mild symptoms of pain, depression and sleep impairment, was considered.No evidence of associations with FM per se were detected, using either a family-based approach or SNPs combination analyses. However, considering the subgroups of FM patients, the SNP rs6454674 (CNR1, cannabinoid receptor 1 gene) was found as a potential genetic marker of FM correlated with depression (p<.001).RESULTSNo evidence of associations with FM per se were detected, using either a family-based approach or SNPs combination analyses. However, considering the subgroups of FM patients, the SNP rs6454674 (CNR1, cannabinoid receptor 1 gene) was found as a potential genetic marker of FM correlated with depression (p<.001).No significant associations using either the family-based analysis or the SNPs combination tests dissociated FM patients and their healthy relatives. FM patients with and without depression showed a significant difference in the genotypic distribution related to the SNP rs6454674 in the cannabinoid receptor 1 gene (CNR1) indicating that FM is not a homogenous disorder.CONCLUSIONSNo significant associations using either the family-based analysis or the SNPs combination tests dissociated FM patients and their healthy relatives. FM patients with and without depression showed a significant difference in the genotypic distribution related to the SNP rs6454674 in the cannabinoid receptor 1 gene (CNR1) indicating that FM is not a homogenous disorder. |
| Author | González-Villar, Alberto Triñanes, Yolanda Arendt-Nielsen, Lars Carrillo-de-la-Peña, Maria Teresa Pidal-Miranda, Marina Gerra, Maria Carla Søkilde Pedersen, Inge Walther, Donna Donnini, Claudia Moeller, Gert Lykke Romero-Yuste, Susana Arias-Gómez, Manuel Manfredini, Matteo |
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| Title | A family-based study to identify genetic biomarkers of fibromyalgia: consideration of patients' subgroups |
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