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Biology subjects

Langefeld, C.

Publications and source records attributed to Langefeld, C..

4 recordsLinked to original sources

Identification of a regulatory pathway governing TRAF1 via an arthritis-associated non-coding variant

TRAF1/C5 was among the first loci shown to confer risk for inflammatory arthritis in the absence of an associated coding variant, but its genetic mechanism remains undefined. Using ImmunoChip data from 3,939 juvenile idiopathic arthritis (JIA) patients and 14,412 controls, we identified 132 plausible common non-coding variants, reduced serially by SNP-seq, electrophoretic mobility shift, and luciferase studies to the single variant rs7034653 in the third intron of TRAF1. Genetically manipulated experimental cells and primary monocytes from genotyped donors establish that the risk G allele reduces binding of Fos-Related Antigen 2 (FRA2), resulting in reduced TRAF1 expression and enhanced TNF production. Conditioning on this variant eliminates attributable risk for rheumatoid arthritis, implicating a mechanism shared across the arthritis spectrum. These findings reveal that rs7034653, FRA2, and TRAF1 mediate a pathway through which a non-coding causal variant drives risk of inflammatory arthritis in children and adults.

genetics↗

Sex and genetic specific effects on behavioral, but not metabolic, responses to a high fat diet in heterogeneous stock rats

Obesity is a growing epidemic associated with a range of comorbidities, including anxiety and depression. Genetics and environmental factors such as diet contribute to both adiposity and anxiety/depression. Heterogeneous stock (HS) rats are an outbred colony and useful for genetic mapping of complex traits. We have previously shown that HS male rats exhibit worsened metabolic and behavioral health in response to high fat diet (HFD). This study aims to determine if females have similar response to diet and if response to diet interacts with genetic background. We measured multiple metabolic (body weight, fat pad weight, glucose tolerance, fasting glucose and insulin) and behavioral (elevated plus maze, open field test, and forced swim test) outcomes in a large cohort of male and female rats on either HFD or low fat diet (LFD). We estimated overall heritability as well as heritability of response to diet for each outcome. Both sexes showed worsened metabolic measures when fed HFD compared to LFD. In contrast, only males exhibited altered behavioral responses to HFD relative to LFD, with no effect in females. Most metabolic and behavioral measures showed overall heritability in both sexes. In contrast, although there was some evidence for gene by diet (GxD) interactions for behavioral measures in males, GxD interactions were generally not found for the metabolic measures. These data demonstrate an important role of diet, sex and genetics in metabolic and behavioral phenotypes in HS rats, with a potential role of gene by diet interactions for behavioral outcomes only in males.

genetics↗

Transcriptome-wide Analyses of Adipose Tissue in Outbred Rats Reveal Genetic Regulatory Mechanisms Relevant for Human Obesity

Transcriptomic analysis in metabolically active tissues allows a systems genetics approach to identify causal genes and networks involved in metabolic disease. Outbred heterogeneous stock (HS) rats are used for genetic mapping of complex traits, but to-date, a systems genetics analysis of metabolic tissues has not been done. We investigated whether adiposity-associated genes and gene co-expression networks in outbred heterogeneous stock (HS) rats overlap those found in humans. We analyzed RNAseq data from adipose tissue of 415 male HS rats, correlated these transcripts with body weight (BW) and compared transcriptome signatures to two human cohorts: the African American Genetics of Metabolism and Expression and Metabolic Syndrome in Men. We used weighted gene co-expression network analysis to identify adiposity-associated gene networks and mediation analysis to identify genes under genetic control whose expression drives adiposity. We identified 554 orthologous "consensus genes" whose expression correlates with BW in the rat and with body mass index (BMI) in both human cohorts. Consensus genes fell within eight co-expressed networks and were enriched for genes involved in immune system function, cell growth, extracellular matrix organization and lipid metabolic processes. We identified 19 consensus genes for which genetic variation may influence BW via their expression, including those involved in lipolysis (e.g., Hcar1), inflammation (e.g., Rgs1), adipogenesis (e.g., Tmem120b) or no previously known role in obesity (e.g., St14, Msa4a6). Strong concordance between HS rat and human BW/BMI associated transcripts demonstrates translational utility of the rat model, while identification of novel genes expands our knowledge of the genetics underlying obesity.

genomics↗

The Subtype Specificity of Genetic Loci Associated with Stroke in 16,664 cases and 32,792 controls

BackgroundGenome-wide association studies have identified multiple loci associated with stroke. However, the specific stroke subtypes affected, and whether loci influence both ischaemic and haemorrhagic stroke, remains unknown. For loci associated with stroke, we aimed to infer the combination of stroke subtypes likely to be affected, and in doing so assess the extent to which such loci have homogeneous effects across stroke subtypes.\n\nMethodsWe performed Bayesian multinomial regression in 16,664 stroke cases and 32,792 controls of European ancestry to determine the most likely combination of stroke subtypes affected for loci with published genome-wide stroke associations, using model selection. Cases were subtyped under two commonly used stroke classification systems, Trial of Org 10172 Acute Stroke Treatment (TOAST) and Causative Classification of Stroke (CCS). All individuals had genotypes imputed to the Haplotype Reference Consortium 1.1 Panel.\n\nResultsSixteen loci were considered for analysis. Seven loci influenced both haemorrhagic and ischaemic stroke, three of which influenced ischaemic and haemorrhagic subtypes under both TOAST and CCS. Under CCS, 4 loci influenced both small vessel stroke and intracerebral haemorrhage. An EDNRA locus demonstrated opposing effects on ischaemic and haemorrhagic stroke. No loci were predicted to influence all stroke subtypes in the same direction and only one locus (12q24) was predicted to influence all ischaemic stroke subtypes.\n\nConclusionsHeterogeneity in the influence of stroke-associated loci on stroke subtypes is pervasive, reflecting differing causal pathways. However, overlap exists between haemorrhagic and ischaemic stroke, which may reflect shared pathobiology predisposing to small vessel arteriopathy. Stroke is a complex, heterogeneous disorder requiring tailored analytic strategies to decipher genetic mechanisms.

genetics↗