1. |
|
|
2. |
|
|
3. |
- Machiela, Mitchell J., et al.
(författare)
-
Characterization of Large Structural Genetic Mosaicism in Human Autosomes
- 2015
-
Ingår i: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 96:3, s. 487-497
-
Tidskriftsartikel (refereegranskat)abstract
- Analyses of genome-wide association study (GWAS) data have revealed that detectable genetic mosaicism involving large (>2 Mb) structural autosomal alterations occurs in a fraction of individuals. We present results for a set of 24,849 genotyped individuals (total GWAS set II [TGSII]) in whom 341 large autosomal abnormalities were observed in 168 (0.68%) individuals. Merging data from the new TGSII set with data from two prior reports (the Gene-Environment Association Studies and the total GWAS set I) generated a large dataset of 127,179 individuals; we then conducted a meta-analysis to investigate the patterns of detectable autosomal mosaicism (n = 1,315 events in 925 [0.73%] individuals). Restricting to events >2 Mb in size, we observed an increase in event frequency as event size decreased. The combined results underscore that the rate of detectable mosaicism increases with age (p value = 5.5 x 3 10(-31)) and is higher in men (p value = 0.002) but lower in participants of African ancestry (p value = 0.003). In a subset of 47 individuals from whom serial samples were collected up to 6 years apart, complex changes were noted over time and showed an overall increase in the proportion of mosaic cells as age increased. Our large combined sample allowed for a unique ability to characterize detectable genetic mosaicism involving large structural events and strengthens the emerging evidence of non-random erosion of the genome in the aging population.
|
|
4. |
- 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.
|
|
5. |
|
|
6. |
|
|
7. |
- Kaaks, Rudolf, et al.
(författare)
-
Lag Times between Lymphoproliferative Disorder and Clinical Diagnosis of Chronic Lymphocytic Leukemia : A Prospective Analysis Using Plasma Soluble CD23
- 2015
-
Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - 1055-9965 .- 1538-7755. ; 24:3, s. 538-545
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Chronic lymphocytic leukemia (CLL) is a chronic disease that often progresses slowly from a precursor stage, monoclonal B-cell lymphocytosis (MBL), and that can remain undiagnosed for a long time. Methods: Within the European Prospective Investigation into Cancer cohort, we measured prediagnostic plasma sCD23 for 179 individuals who eventually were diagnosed with CLL and an equal number of matched control subjects who remained free of cancer. Results: In a very large proportion of CLL patients' plasma sCD23 was clearly elevated 7 or more years before diagnosis. Considering sCD23 as a disease predictor, the area under the ROC curve (AUROC) was 0.95 [95% confidence interval (CI), 0.90-1.00] for CLL diagnosed within 0.1 to 2.7 years after blood measurement, 0.90 (95% CI, 0.86-0.95) for diagnosis within 2.8 to 7.3 years, and 0.76 (95% CI, 0.65-0.86) for CLL diagnosed between 7.4 and 12.5 years. Even at a 7.4-year and longer time interval, elevated plasma sCD23 could predict a later clinical diagnosis of CLL with 100% specificity at > 45% sensitivity. Conclusions: Our findings provide unique documentation for the very long latency times during which measurable B-cell lymphoproliferative disorder exists before the clinical manifestation of CLL. Impact: Our findings have relevance for the interpretation of prospective epidemiologic studies on the causes of CLL in terms of reverse causation bias. The lag times indicate a time frame within which an early detection of CLL would be theoretically possible. (c) 2014 AACR.
|
|
8. |
- Lupo, Philip J., et al.
(författare)
-
Family history of cancer and childhood rhabdomyosarcoma : a report from the Children's Oncology Group and the Utah Population Database
- 2015
-
Ingår i: Cancer Medicine. - : Wiley. - 2045-7634. ; 4:5, s. 781-790
-
Tidskriftsartikel (refereegranskat)abstract
- Relatively little is known about the epidemiology and factors underlying susceptibility to childhood rhabdomyosarcoma (RMS). To better characterize genetic susceptibility to childhood RMS, we evaluated the role of family history of cancer using data from the largest case-control study of RMS and the Utah Population Database (UPDB). RMS cases (n=322) were obtained from the Children's Oncology Group (COG). Population-based controls (n=322) were pair-matched to cases on race, sex, and age. Conditional logistic regression was used to evaluate the association between family history of cancer and childhood RMS. The results were validated using the UPDB, from which 130 RMS cases were identified and matched to controls (n=1300) on sex and year of birth. The results were combined to generate summary odds ratios (ORs) and 95% confidence intervals (CI). Having a first-degree relative with a cancer history was more common in RMS cases than controls (ORs=1.39, 95% CI: 0.97-1.98). Notably, this association was stronger among those with embryonal RMS (ORs=2.44, 95% CI: 1.54-3.86). Moreover, having a first-degree relative who was younger at diagnosis of cancer (<30years) was associated with a greater risk of RMS (ORs=2.37, 95% CI: 1.34-4.18). In the largest analysis of its kind, we found that most children diagnosed with RMS did not have a family history of cancer. However, our results indicate an increased risk of RMS (particularly embryonal RMS) in children who have a first-degree relative with cancer, and among those whose relatives were diagnosed with cancer at <30years of age.
|
|