Valistuksen vastapainot

Esko Rahikainen ja Timo Kaitaro

Integration of genome-wide association studies with biological knowledge identifies six novel genes related to kidney function.

In conducting genome-wide association studies (GWAS), analytical approaches leveraging biological information may further understanding of the pathophysiology of clinical traits. To discover novel associations with estimated glomerular filtration rate (eGFR), a measure of kidney function, we developed a strategy for integrating prior biological knowledge into the existing GWAS data for eGFR from the CKDGen Consortium. Our strategy focuses on single nucleotide polymorphism (SNPs) in genes that are connected by functional evidence, determined by literature mining and gene ontology (GO) hierarchies, to genes near previously validated eGFR associations. It then requires association thresholds consistent with multiple testing, and finally evaluates novel candidates by independent replication. Among the samples of European ancestry, we identified a genome-wide significant SNP in FBXL20 (P = 5.6 × 10(-9)) in meta-analysis of all available data, and additional SNPs at the INHBC, LRP2, PLEKHA1, SLC3A2 and SLC7A6 genes meeting multiple-testing corrected significance for replication and overall P-values of 4.5 × 10(-4)-2.2 × 10(-7). Neither the novel PLEKHA1 nor FBXL20 associations, both further supported by association with eGFR among African Americans and with transcript abundance, would have been implicated by eGFR candidate gene approaches. LRP2, encoding the megalin receptor, was identified through connection with the previously known eGFR gene DAB2 and extends understanding of the megalin system in kidney function. These findings highlight integration of existing genome-wide association data with independent biological knowledge to uncover novel candidate eGFR associations, including candidates lacking known connections to kidney-specific pathways. The strategy may also be applicable to other clinical phenotypes, although more testing will be needed to assess its potential for discovery in general.

Tiedonsaannin turvaaminen

Esko Häkli

Human chorionic gonadotropin in pregnancy and maternal risk of breast cancer.

Full-term pregnancies are associated with long-term reductions in maternal risk of breast cancer, but the biological determinants of the protection are unknown. Experimental observations suggest that human chorionic gonadotropin (hCG), a major hormone of pregnancy, could play a role in this association. A case-control study (242 cases and 450 controls) nested within the Northern Sweden Maternity Cohort included women who had donated a blood sample during the first trimester of a first full-term pregnancy. Total hCG was determined on Immulite 2000 analyzer. Odds ratios (OR) and 95% confidence intervals (CI) were estimated through conditional logistic regression. Maternal breast cancer risk decreased with increasing hCG (upper tertile OR, 0.67; CI, 0.46-0.99), especially for pregnancies before age 25 (upper tertile OR, 0.41; CI, 0.21-0.80). The association diverged according to age at diagnosis: risk was reduced after age 40 (upper tertile OR, 0.60; CI, 0.39-0.91) and seemed to increase before age 40 (upper tertile OR, 1.78; CI, 0.72-4.38). Risk was reduced among those diagnosed 10 years or longer after blood draw (upper tertile OR, 0.60; CI, 0.40-0.90), but not so among those diagnosed within 10 years (upper tertile OR, 4.33; CI, 0.86-21.7). These observations suggest that the association between pregnancy hCG and subsequent maternal risk of breast cancer is modified by age at diagnosis. Although the hormone seems to be a determinant of the reduced risk around or after age 50, it might not confer protection against, or it could even increase the risk of, cancers diagnosed in the years immediately following pregnancy.

Novel loci affecting iron homeostasis and their effects in individuals at risk for hemochromatosis

Variation in body iron is associated with or causes diseases, including anaemia and iron overload. Here, we analyse genetic association data on biochemical markers of iron status from 11 European-population studies, with replication in eight additional cohorts (total up to 48,972 subjects). We find 11 genome-wide-significant (P<5 × 10(-8)) loci, some including known iron-related genes (HFE, SLC40A1, TF, TFR2, TFRC, TMPRSS6) and others novel (ABO, ARNTL, FADS2, NAT2, TEX14). SNPs at ARNTL, TF, and TFR2 affect iron markers in HFE C282Y homozygotes at risk for hemochromatosis. There is substantial overlap between our iron loci and loci affecting erythrocyte and lipid phenotypes. These results will facilitate investigation of the roles of iron in disease.