Human and mouse neuroinflammation markers in Niemann‐Pick disease, type C1

Niemann‐Pick disease, type C1 (NPC1) is an autosomal recessive lipid storage disorder in which a pathological cascade, including neuroinflammation occurs. While data demonstrating neuroinflammation is prevalent in mouse models, data from NPC1 patients is lacking. The current study focuses on identifying potential markers of neuroinflammation in NPC1 from both the Npc1 mouse model and NPC1 patients. We identified in the mouse model significant changes in expression of genes associated with inflammation and compared these results to the pattern of expression in human cortex and cerebellar tissue. From gene expression array analysis, complement 3 (C3) was increased in mouse and human post‐mortem NPC1 brain tissues. We also characterized protein levels of inflammatory markers in cerebrospinal fluid (CSF) from NPC1 patients and controls. We found increased levels of interleukin 3, chemokine (C‐X‐C motif) ligand 5, interleukin 16 and chemokine ligand 3 (CCL3), and decreased levels of interleukin 4, 10, 13 and 12p40 in CSF from NPC1 patients. CSF markers were evaluated with respect to phenotypic severity. Miglustat treatment in NPC1 patients slightly decreased IL‐3, IL‐10 and IL‐13 CSF levels; however, further studies are needed to establish a strong effect of miglustat on inflammation markers. The identification of inflammatory markers with altered levels in the cerebrospinal fluid of NPC1 patients may provide a means to follow secondary events in NPC1 disease during therapeutic trials.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147148/1/jimd0083.pd

Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer

Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (P<5 × 10−8) with oestrogen receptor (ER)-negative breast cancer and BRCA1-associated breast cancer risk. In this study, to identify new ER-negative susceptibility loci, we performed a meta-analysis of 11 genome-wide association studies (GWAS) consisting of 4,939 ER-negative cases and 14,352 controls, combined with 7,333 ER-negative cases and 42,468 controls and 15,252 BRCA1 mutation carriers genotyped on the iCOGS array. We identify four previously unidentified loci including two loci at 13q22 near KLF5, a 2p23.2 locus near WDR43 and a 2q33 locus near PPIL3 that display genome-wide significant associations with ER-negative breast cancer. In addition, 19 known breast cancer risk loci have genome-wide significant associations and 40 had moderate associations (P<0.05) with ER-negative disease. Using functional and eQTL studies we implicate TRMT61B and WDR43 at 2p23.2 and PPIL3 at 2q33 in ER-negative breast cancer aetiology. All ER-negative loci combined account for ∼11% of familial relative risk for ER-negative disease and may contribute to improved ER-negative and BRCA1 breast cancer risk prediction

Genome-Wide Association Study in BRCA1 Mutation Carriers Identifies Novel Loci Associated with Breast and Ovarian Cancer Risk

BRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer), with a further replication in an additional sample of 2,646 BRCA1 carriers. We identified a novel breast cancer risk modifier locus at 1q32 for BRCA1 carriers (rs2290854, P = 2.7×10-8, HR = 1.14, 95% CI: 1.09-1.20). In addition, we identified two novel ovarian cancer risk modifier loci: 17q21.31 (rs17631303, P = 1.4×10-8, HR = 1.27, 95% CI: 1.17-1.38) and 4q32.3 (rs4691139, P = 3.4×10-8, HR = 1.20, 95% CI: 1.17-1.38). The 4q32.3 locus was not associated with ovarian cancer risk in the general population or BRCA2 carriers, suggesting a BRCA1-specific associat

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer

Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (PPeer reviewe