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| 23. |
- Ge, R, et al.
(författare)
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Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain: Algorithm Benchmarking and Model Optimization
- 2023
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Ingår i: bioRxiv : the preprint server for biology. - : Cold Spring Harbor Laboratory.
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Background: Normative modeling is a statistical approach to quantify the degree to which a particular individual-level measure deviates from the pattern observed in a normative reference population. When applied to human brain morphometric measures it has the potential to inform about the significance of normative deviations for health and disease. Normative models can be implemented using a variety of algorithms that have not been systematically appraised. Methods: To address this gap, eight algorithms were compared in terms of performance and computational efficiency using brain regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) collated from 87 international MRI datasets. Performance was assessed with the mean absolute error (MAE) and computational efficiency was inferred from central processing unit (CPU) time. The algorithms evaluated were Ordinary Least Squares Regression (OLSR), Bayesian Linear Regression (BLR), Generalized Additive Models for Location, Scale, and Shape (GAMLSS), Parametric Lambda, Mu, Sigma (LMS), Gaussian Process Regression (GPR), Warped Bayesian Linear Regression (WBLG), Hierarchical Bayesian Regression (HBR), and Multivariable Fractional Polynomial Regression (MFPR). Model optimization involved testing nine covariate combinations pertaining to acquisition features, parcellation software versions, and global neuroimaging measures (i.e., total intracranial volume, mean cortical thickness, and mean cortical surface area). Findings: Statistical comparisons across models at PFDR<0.05 indicated that the MFPR-derived sex- and region-specific models with nonlinear polynomials for age and linear effects of global measures had superior predictive accuracy; the range of the MAE of the models of regional subcortical volumes was 70-520 mm3 and the corresponding ranges for regional cortical thickness and regional cortical surface area were 0.09-0.26 mm and 24-560 mm2, respectively. The MFPR-derived models were also computationally more efficient with a CPU time below one second compared to a range of 2 seconds to 60 minutes for the other algorithms. The performance of all sex- and region-specific MFPR models plateaued at sample sizes exceeding 3,000 and showed comparable MAEs across distinct 10-year age-bins covering the human lifespan. Interpretation: These results provide an empirically benchmarked framework for normative modeling of brain morphometry that is useful for interpreting prior literature and supporting future study designs. The model and tools described here are freely available through CentileBrain (https://centilebrain.org/), a user-friendly web platform.
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- Jakubowska, A, et al.
(författare)
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Association of PHB 1630 C andgt; T and MTHFR 677 C andgt; T polymorphisms with breast and ovarian cancer risk in BRCA1/2 mutation carriers: results from a multicenter study
- 2012
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Ingår i: British Journal of Cancer. - : Cancer Research UK / Nature Publishing Group. - 0007-0920 .- 1532-1827. ; 106:12, s. 2016-2024
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The variable penetrance of breast cancer in BRCA1/2 mutation carriers suggests that other genetic or environmental factors modify breast cancer risk. Two genes of special interest are prohibitin (PHB) and methylene-tetrahydrofolate reductase (MTHFR), both of which are important either directly or indirectly in maintaining genomic integrity. less thanbrgreater than less thanbrgreater thanMETHODS: To evaluate the potential role of genetic variants within PHB and MTHFR in breast and ovarian cancer risk, 4102 BRCA1 and 2093 BRCA2 mutation carriers, and 6211 BRCA1 and 2902 BRCA2 carriers from the Consortium of Investigators of Modifiers of BRCA1 and BRCA2 (CIMBA) were genotyped for the PHB 1630 Candgt;T (rs6917) polymorphism and the MTHFR 677 Candgt;T (rs1801133) polymorphism, respectively. less thanbrgreater than less thanbrgreater thanRESULTS: There was no evidence of association between the PHB 1630 Candgt;T and MTHFR 677 Candgt;T polymorphisms with either disease for BRCA1 or BRCA2 mutation carriers when breast and ovarian cancer associations were evaluated separately. Analysis that evaluated associations for breast and ovarian cancer simultaneously showed some evidence that BRCA1 mutation carriers who had the rare homozygote genotype (TT) of the PHB 1630 Candgt;T polymorphism were at increased risk of both breast and ovarian cancer (HR 1.50, 95% CI 1.10-2.04 and HR 2.16, 95% CI 1.24-3.76, respectively). However, there was no evidence of association under a multiplicative model for the effect of each minor allele. less thanbrgreater than less thanbrgreater thanCONCLUSION: The PHB 1630TT genotype may modify breast and ovarian cancer risks in BRCA1 mutation carriers. This association need to be evaluated in larger series of BRCA1 mutation carriers.
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| 25. |
- Lawrenson, Kate, et al.
(författare)
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Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus
- 2016
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10-20), ER-negative BC (P=1.1 × 10-13), BRCA1-associated BC (P=7.7 × 10-16) and triple negative BC (P-diff=2 × 10-5). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P=2 × 10-3) and ABHD8 (P<2 × 10-3). Chromosome conformation capture identifies interactions between four candidate SNPs and ABHD8, and luciferase assays indicate six risk alleles increased transactivation of the ADHD8 promoter. Targeted deletion of a region containing risk SNP rs56069439 in a putative enhancer induces ANKLE1 downregulation; and mRNA stability assays indicate functional effects for an ANKLE1 3′-UTR SNP. Altogether, these data suggest that multiple SNPs at 19p13 regulate ABHD8 and perhaps ANKLE1 expression, and indicate common mechanisms underlying breast and ovarian cancer risk.
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