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Background: C-reactive protein (CRP) is a moderately heritable marker of systemic inflammation that is associated with adverse physical and mental health outcomes. Identifying factors associated with genetic liability to elevated CRP in childhood may inform our understanding of variability in CRP that could be targeted to prevent and/or delay the onset of related health outcomes.
Methods: We conducted a phenome-wide association study (PheWAS) of genetic risk for elevated CRP (i.e. CRP polygenic risk score [PRS]) among children genetically similar to European ancestry reference populations (median analytic n = 5,509, range = 120-5,556) from the Adolescent Brain and Cognitive Development (ABCD) Study baseline assessment. Associations between CRP PRS and 2,377 psychosocial and neuroimaging phenotypes were estimated using independent mixed effects models nested by recruitment site (or scanner) and family, with ancestral genomic principal components (n = 10), age, and sex, as well as global brain metrics (when relevant) included as fixed effect covariates. Post hoc analyses examined whether: (1) covarying for measured body mass index (BMI) or removing the shared genetic architecture between CRP and BMI altered phenotypic associations, (2) sex moderated CRP PRS associations, and (3) associations were unconfounded by assortative mating or passive gene-environment correlations (using within-family analyses). Multiple testing was adjusted for using Bonferroni and false discovery rate (FDR) correction.
Results: Nine phenotypes were positively associated with CRP PRS after multiple testing correction: five weight- and eating-related phenotypes (e.g. BMI, overeating), three phenotypes related to caregiver somatic problems (e.g. caregiver somatic complaints), as well as weekday video watching (all ps = 1.2 x 10 - 2.5 x 10, all ps = 0.0002-0.05). No neuroimaging phenotypes were associated with CRP PRS (all ps = 0.0003-0.998; all ps = 0.08-0.998) after correction for multiple testing. Eating and weight-related phenotypes remained associated with CRP PRS in within-family analyses. Covarying for BMI resulted in largely consistent results, and sex did not moderate any CRP PRS associations. Removing the shared genetic variance between CRP and BMI attenuated all relationships; associations with weekday video watching, caregiver somatic problems and caregiver report that the child is overweight remained significant while associations with waist circumference, weight, and caregiver report that child overeats did not.
Discussion: Genetic liability to elevated CRP is associated with higher weight, eating, and weekday video watching during childhood as well as caregiver somatic problems. These associations were consistent with direct genetic effects (i.e., not solely due to confounding factors like passive gene-environment correlations) and were independent of measured BMI. The majority of associations with weight and eating phenotypes were attributable to shared genetic architecture between BMI and inflammation. The relationship between genetics and heightened inflammation in later life may be partially attributable to modifiable behaviors (e.g. weight and activity levels) that are expressed as early as childhood.
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http://dx.doi.org/10.1016/j.bbi.2025.04.012 | DOI Listing |
Am J Hum Genet
August 2025
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA. Electronic address:
Inflammation is a critical component of chronic diseases, aging progression, and lifespan. Omics signatures may characterize inflammation status beyond blood biomarkers. We leveraged genetics (polygenic risk score [PRS]), metabolomics (metabolomic risk score [MRS]), and epigenetics (epigenetic risk score [ERS]) to build multi-omics-multi-marker risk scores for inflammation status represented by the level of circulating C-reactive protein (CRP), interleukin 6 (IL-6), and tumor necrosis factor alpha (TNF-α).
View Article and Find Full Text PDFPLoS One
July 2025
Vestfold Hospital Trust, Central Laboratory, Tønsberg, Norway.
Background: Understanding the relationship between central adiposity and health outcomes in children is crucial for early prevention of non-communicable diseases (NCDs). Waist-to-height ratio (WHtR) has emerged as a key anthropometric measure for predicting cardiovascular and metabolic health risks.
Methods: The objective of this study was to investigate whether WHtR is associated with cardiovascular and metabolic risk markers, including HbA1c, CRP, lipid profiles, blood pressure, ferritin, and iron levels, in healthy children aged 6-12 years.
BMC Endocr Disord
July 2025
Department of Cellular and Molecular Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, PO Box: 141556117, Tehran, Iran.
The prevalence of cardiovascular diseases (CVDs) is increasing in most parts of the world. Several studies suggest that type 2 diabetes mellitus (T2DM) and CVD are induced by lifestyle behaviours and genetic factors. This study investigated the association between a genetic risk score (GRS) and cardio-metabolic risk factors among diabetic patients.
View Article and Find Full Text PDFBiopsychosoc Sci Med
September 2025
Objective: Genetics contributes to elevated body mass index (BMI) in youth. Adolescents experiencing interpersonal stressors (eg, peer victimization or parental criticism) may additionally be at a heightened risk for developing high BMI. However, few studies have examined the additive contributions of genetic factors and interpersonal stressors to BMI.
View Article and Find Full Text PDFCommun Biol
May 2025
Cardiovascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA.
C-reactive protein (CRP) reflects inflammation status and is linked to poor sleep, metabolic and cardiovascular health. Methylation (MRS) and polygenic risk scores (PRS) reflect long-term systemic inflammation, and genetically-determined CRP, respectively. To refine understanding of inflammation-linked sleep and health outcomes, we construct PRS-CRPs using GWAS summary statistics and a previously-developed MRS-CRP in the Hispanic Community Health Study/Study of Latinos.
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