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Träfflista för sökning "WFRF:(LaCroix Andrea Z) ;lar1:(lu)"

Sökning: WFRF:(LaCroix Andrea Z) > Lunds universitet

  • Resultat 1-7 av 7
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1.
  • Arslan, Alan A., et al. (författare)
  • Anthropometric Measures, Body Mass Index, and Pancreatic Cancer A Pooled Analysis From the Pancreatic Cancer Cohort Consortium (PanScan)
  • 2010
  • Ingår i: Archives of Internal Medicine. - 0003-9926. ; 170:9, s. 791-802
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Obesity has been proposed as a risk factor for pancreatic cancer. Methods: Pooled data were analyzed from the National Cancer Institute Pancreatic Cancer Cohort Consortium (PanScan) to study the association, between prediagnostic anthropometric measures and risk of pancreatic cancer. PanScan applied a nested case-control study design and included 2170 cases and 2209 control subjects. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using unconditional logistic regression for cohort-specific quartiles of body mass index (BMI [calculated as weight in kilograms divided by height in meters squared]), weight, height, waist circumference, and waist to hip ratio as well as conventional BMI categories (underweight, <18.5; normal weight, 18.5-24.9; overweight, 25.0-29.9; obese, 30.0-34.9; and severely obese, >= 35.0). Models were adjusted for potential confounders. Results: In all of the participants, a positive association between increasing BMI and risk of pancreatic cancer was observed (adjusted OR for the highest vs lowest BMI guartile, 1.33; 95% Cl, 1.12-1.58; P-trend<.001). In men, the adjusted OR for pancreatic cancer for the highest vs lowest quartile of BMI was 1.33 (95% Cl, 1.04-1.69; P-trend<.03), and in women it was 1.34 (95% Cl, 1.05-1.70; P-trend=.01). Increased waist to hip ratio was associated with increased risk of pancreatic cancer in women (adjusted OR for the highest vs lowest quartile, 1.87; 95% Cl, 1.31-2.69; P-trend=.003) but less so in men. Conclusions: These findings provide strong support for a positive association between BMI and pancreatic cancer risk. In addition, centralized fat distribution may increase pancreatic cancer risk, especially in women. Arch Intern Med. 2010;170(9):791 -802
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2.
  • Asselbergs, Folkert W., et al. (författare)
  • Large-Scale Gene-Centric Meta-analysis across 32 Studies Identifies Multiple Lipid Loci
  • 2012
  • Ingår i: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297. ; 91:5, s. 823-838
  • Tidskriftsartikel (refereegranskat)abstract
    • Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), can be identified by a dense gene-centric approach. Our meta-analysis of 32 studies in 66,240 individuals of European ancestry was based on the custom similar to 50,000 SNP genotyping array (the ITMAT-Broad-CARe array) covering similar to 2,000 candidate genes. SNP-lipid associations were replicated either in a cohort comprising an additional 24,736 samples or within the Global Lipid Genetic Consortium. We identified four, six, ten, and four unreported SNPs in established lipid genes for HDL-C, LDL-C, TC, and TGs, respectively. We also identified several lipid-related SNPs in previously unreported genes: DGAT2, HCAR2, GPIHBP1, PPARG, and FTO for HDL-C; SOCS3, APOH, SPTY2D1, BRCA2, and VLDLR for LDL-C; SOCS3, UGT1A1, BRCA2, UBE3B, FCGR2A, CHUK, and INSIG2 for TC; and SERPINF2, C4B, GCK, GATA4, INSR, and LPAL2 for TGs. The proportion of explained phenotypic variance in the subset of studies providing individual-level data was 9.9% for HDL-C, 9.5% for LDL-C, 10.3% for TC, and 8.0% for TGs. This large meta-analysis of lipid phenotypes with the use of a dense gene-centric approach identified multiple SNPs not previously described in established lipid genes and several previously unknown loci. The explained phenotypic variance from this approach was comparable to that from a meta-analysis of GWAS data, suggesting that a focused genotyping approach can further increase the understanding of heritability of plasma lipids.
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3.
  • Estrada, Karol, et al. (författare)
  • Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture.
  • 2012
  • Ingår i: Nature genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 44:5, s. 491-501
  • Tidskriftsartikel (refereegranskat)abstract
    • Bone mineral density (BMD) is the most widely used predictor of fracture risk. We performed the largest meta-analysis to date on lumbar spine and femoral neck BMD, including 17 genome-wide association studies and 32,961 individuals of European and east Asian ancestry. We tested the top BMD-associated markers for replication in 50,933 independent subjects and for association with risk of low-trauma fracture in 31,016 individuals with a history of fracture (cases) and 102,444 controls. We identified 56 loci (32 new) associated with BMD at genome-wide significance (P < 5 × 10(-8)). Several of these factors cluster within the RANK-RANKL-OPG, mesenchymal stem cell differentiation, endochondral ossification and Wnt signaling pathways. However, we also discovered loci that were localized to genes not known to have a role in bone biology. Fourteen BMD-associated loci were also associated with fracture risk (P < 5 × 10(-4), Bonferroni corrected), of which six reached P < 5 × 10(-8), including at 18p11.21 (FAM210A), 7q21.3 (SLC25A13), 11q13.2 (LRP5), 4q22.1 (MEPE), 2p16.2 (SPTBN1) and 10q21.1 (DKK1). These findings shed light on the genetic architecture and pathophysiological mechanisms underlying BMD variation and fracture susceptibility.
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4.
  • Ganesh, Santhi K., et al. (författare)
  • Loci influencing blood pressure identified using a cardiovascular gene-centric array
  • 2013
  • Ingår i: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 22:8, s. 1663-1678
  • Tidskriftsartikel (refereegranskat)abstract
    • Blood pressure (BP) is a heritable determinant of risk for cardiovascular disease (CVD). To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP) and pulse pressure (PP), we genotyped 50 000 single-nucleotide polymorphisms (SNPs) that capture variation in 2100 candidate genes for cardiovascular phenotypes in 61 619 individuals of European ancestry from cohort studies in the USA and Europe. We identified novel associations between rs347591 and SBP (chromosome 3p25.3, in an intron of HRH1) and between rs2169137 and DBP (chromosome1q32.1 in an intron of MDM4) and between rs2014408 and SBP (chromosome 11p15 in an intron of SOX6), previously reported to be associated with MAP. We also confirmed 10 previously known loci associated with SBP, DBP, MAP or PP (ADRB1, ATP2B1, SH2B3/ATXN2, CSK, CYP17A1, FURIN, HFE, LSP1, MTHFR, SOX6) at array-wide significance (P 2.4 10(6)). We then replicated these associations in an independent set of 65 886 individuals of European ancestry. The findings from expression QTL (eQTL) analysis showed associations of SNPs in the MDM4 region with MDM4 expression. We did not find any evidence of association of the two novel SNPs in MDM4 and HRH1 with sequelae of high BP including coronary artery disease (CAD), left ventricular hypertrophy (LVH) or stroke. In summary, we identified two novel loci associated with BP and confirmed multiple previously reported associations. Our findings extend our understanding of genes involved in BP regulation, some of which may eventually provide new targets for therapeutic intervention.
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6.
  • Wolpin, Brian M., et al. (författare)
  • Variant ABO Blood Group Alleles, Secretor Status, and Risk of Pancreatic Cancer: Results from the Pancreatic Cancer Cohort Consortium
  • 2010
  • Ingår i: Cancer Epidemiology Biomarkers & Prevention. - 1538-7755 .- 1055-9965. ; 19:12, s. 3140-3149
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Subjects with non-O ABO blood group alleles have increased risk of pancreatic cancer. Glycosyltransferase activity is greater for the A(1) versus A(2) variant, whereas O01 and O02 variants are nonfunctioning. We hypothesized: 1) A(1) allele would confer greater risk than A(2) allele, 2) protective effect of the O allele would be equivalent for O01 and O02 variants, 3) secretor phenotype would modify the association with risk. Methods: We determined ABO variants and secretor phenotype from single nucleotide polymorphisms in ABO and FUT2 genes in 1,533 cases and 1,582 controls from 12 prospective cohort studies. Adjusted odds ratios (OR) for pancreatic cancer were calculated using logistic regression. Results: An increased risk was observed in participants with A(1) but not A(2) alleles. Compared with subjects with genotype O/O, genotypes A(2)/O, A(2)/A(1), A(1)/O, and A(1)/A(1) had ORs of 0.96 (95% CI, 0.72-1.26), 1.46 (95% CI, 0.98-2.17), 1.48 (95% CI, 1.23-1.78), and 1.71 (95% CI, 1.18-2.47). Risk was similar for O01 and O02 variant O alleles. Compared with O01/O01, the ORs for each additional allele of O02, A(1), and A(2) were 1.00 (95% CI, 0.87-1.14), 1.38 (95% CI, 1.20-1.58), and 0.96 (95% CI, 0.77-1.20); P-value, O01 versus O02 = 0.94, A(1) versus A(2) = 0.004. Secretor phenotype was not an effect modifier (P-interaction = 0.63). Conclusions: Among participants in a large prospective cohort consortium, ABO allele subtypes corresponding to increased glycosyltransferase activity were associated with increased pancreatic cancer risk. Impact: These data support the hypothesis that ABO glycosyltransferase activity influences pancreatic cancer risk rather than actions of other nearby genes on chromosome 9q34. Cancer Epidemiol Biomarkers Prev; 19(12); 3140-9. (C) 2010 AACR.
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7.
  • Zheng, Hou-Feng, et al. (författare)
  • Whole-genome sequencing identifies EN1 as a determinant of bone density and fracture
  • 2015
  • Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 526:7571, s. 112-
  • Tidskriftsartikel (refereegranskat)abstract
    • The extent to which low-frequency (minor allele frequency (MAF) between 1-5%) and rare (MAF <= 1%) variants contribute to complex traits and disease in the general population is mainly unknown. Bone mineral density (BMD) is highly heritable, a major predictor of osteoporotic fractures, and has been previously associated with common genetic variants(1-8), as well as rare, population specific, coding variants(9). Here we identify novel non-coding genetic variants with large effects on BMD (n(total) = 53,236) and fracture (n(total) = 508,253) in individuals of European ancestry from the general population. Associations for BMD were derived from whole-genome sequencing (n = 2,882 from UK10K (ref. 10); a population-based genome sequencing consortium), whole-exome sequencing (n = 3,549), deep imputation of genotyped samples using a combined UK10K/1000 Genomes reference panel (n = 26,534), and de novo replication genotyping (n = 20,271). We identified a low-frequency non-coding variant near a novel locus, EN1, with an effect size fourfold larger than the mean of previously reported common variants for lumbar spine BMD8 (rs11692564(T), MAF51.6%, replication effect size510.20 s.d., P-meta = 2 x 10(-14)), which was also associated with a decreased risk of fracture (odds ratio = 0.85; P = 2 x 10(-11); ncases = 98,742 and ncontrols = 409,511). Using an En1cre/flox mouse model, we observed that conditional loss of En1 results in low bone mass, probably as a consequence of high bone turnover. We also identified a novel low frequency non-coding variant with large effects on BMD near WNT16 (rs148771817(T), MAF = 1.2%, replication effect size +10.41 s.d., P-meta = 1 x 10(-11)). In general, there was an excess of association signals arising from deleterious coding and conserved non-coding variants. These findings provide evidence that low-frequency non-coding variants have large effects on BMD and fracture, thereby providing rationale for whole-genome sequencing and improved imputation reference panels to study the genetic architecture of complex traits and disease in the general population.
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