1. |
- Romagnoni, A, et al.
(author)
-
Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data
- 2019
-
In: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1, s. 10351-
-
Journal article (peer-reviewed)abstract
- Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers.
|
|
2. |
- Sawcer, Stephen, et al.
(author)
-
Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis
- 2011
-
In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 476:7359, s. 214-219
-
Journal article (peer-reviewed)abstract
- Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis.
|
|
3. |
|
|
4. |
- Craddock, Nick, et al.
(author)
-
Genome-wide association study of CNVs in 16,000 cases of eight common diseases and 3,000 shared controls
- 2010
-
In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 464:7289, s. 713-720
-
Journal article (peer-reviewed)abstract
- Copy number variants (CNVs) account for a major proportion of human genetic polymorphism and have been predicted to have an important role in genetic susceptibility to common disease. To address this we undertook a large, direct genome-wide study of association between CNVs and eight common human diseases. Using a purpose-designed array we typed,19,000 individuals into distinct copy-number classes at 3,432 polymorphic CNVs, including an estimated similar to 50% of all common CNVs larger than 500 base pairs. We identified several biological artefacts that lead to false-positive associations, including systematic CNV differences between DNAs derived from blood and cell lines. Association testing and follow-up replication analyses confirmed three loci where CNVs were associated with disease-IRGM for Crohn's disease, HLA for Crohn's disease, rheumatoid arthritis and type 1 diabetes, and TSPAN8 for type 2 diabetes-although in each case the locus had previously been identified in single nucleotide polymorphism (SNP)-based studies, reflecting our observation that most common CNVs that are well-typed on our array are well tagged by SNPs and so have been indirectly explored through SNP studies. We conclude that common CNVs that can be typed on existing platforms are unlikely to contribute greatly to the genetic basis of common human diseases.
|
|
5. |
|
|
6. |
|
|
7. |
|
|
8. |
|
|
9. |
- Madireddy, L, et al.
(author)
-
A systems biology approach uncovers cell-specific gene regulatory effects of genetic associations in multiple sclerosis
- 2019
-
In: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 2236-
-
Journal article (peer-reviewed)abstract
- Genome-wide association studies (GWAS) have identified more than 50,000 unique associations with common human traits. While this represents a substantial step forward, establishing the biology underlying these associations has proven extremely difficult. Even determining which cell types and which particular gene(s) are relevant continues to be a challenge. Here, we conduct a cell-specific pathway analysis of the latest GWAS in multiple sclerosis (MS), which had analyzed a total of 47,351 cases and 68,284 healthy controls and found more than 200 non-MHC genome-wide associations. Our analysis identifies pan immune cell as well as cell-specific susceptibility genes in T cells, B cells and monocytes. Finally, genotype-level data from 2,370 patients and 412 controls is used to compute intra-individual and cell-specific susceptibility pathways that offer a biological interpretation of the individual genetic risk to MS. This approach could be adopted in any other complex trait for which genome-wide data is available.
|
|
10. |
|
|
11. |
- Beecham, Ashley H, et al.
(author)
-
Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis.
- 2013
-
In: Nature genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 45:11, s. 1353-60
-
Journal article (peer-reviewed)abstract
- Using the ImmunoChip custom genotyping array, we analyzed 14,498 subjects with multiple sclerosis and 24,091 healthy controls for 161,311 autosomal variants and identified 135 potentially associated regions (P < 1.0 × 10(-4)). In a replication phase, we combined these data with previous genome-wide association study (GWAS) data from an independent 14,802 subjects with multiple sclerosis and 26,703 healthy controls. In these 80,094 individuals of European ancestry, we identified 48 new susceptibility variants (P < 5.0 × 10(-8)), 3 of which we found after conditioning on previously identified variants. Thus, there are now 110 established multiple sclerosis risk variants at 103 discrete loci outside of the major histocompatibility complex. With high-resolution Bayesian fine mapping, we identified five regions where one variant accounted for more than 50% of the posterior probability of association. This study enhances the catalog of multiple sclerosis risk variants and illustrates the value of fine mapping in the resolution of GWAS signals.
|
|
12. |
|
|
13. |
|
|
14. |
- Akesson, E, et al.
(author)
-
A genome-wide screen for linkage in Nordic sib-pairs with multiple sclerosis
- 2002
-
In: Genes and Immunity. - : Springer Science and Business Media LLC. - 1476-5470 .- 1466-4879. ; 3:5, s. 279-285
-
Journal article (peer-reviewed)abstract
- Genetic factors influence susceptibility to multiple sclerosis but the responsible genes remain largely undefined, association with MHC class II alleles being the only established genetic feature of the disease. The Nordic countries have a high prevalence of multiple sclerosis, and to further explore the genetic background of the disease, we have carried out a genome-wide screen for linkage in 136 sibling-pairs with multiple sclerosis from Denmark, Finland, Norway and Sweden by typing 399 microsatellite markers. Seventeen regions where the lod score exceeds the nominal 5% significance threshold (0.7) were identified-1q11-24, 2q24-32, 3p26.3, 3q21.1, 4q12, 6p25.3, 6p21-22, 6q21, 9q34.3, 10p15, 10p12-13, 11p15.5, 12q21.3, 16p13.3, 17q25.3, 22q12-13 and Xp22.3. Although none of these regions reaches the level of genome-wide significance, the number observed exceeds the 10 that would be expected by chance alone. Our results significantly add to the growing body of linkage data relating to multiple sclerosis.
|
|
15. |
|
|
16. |
- Cronin, O., et al.
(author)
-
Role of the Microbiome in Regulating Bone Metabolism and Susceptibility to Osteoporosis
- 2022
-
In: Calcified Tissue International. - : Springer Science and Business Media LLC. - 0171-967X .- 1432-0827. ; 110:3, s. 273-284
-
Journal article (peer-reviewed)abstract
- The human microbiota functions at the interface between diet, medication-use, lifestyle, host immune development and health. It is therefore closely aligned with many of the recognised modifiable factors that influence bone mass accrual in the young, and bone maintenance and skeletal decline in older populations. While understanding of the relationship between micro-organisms and bone health is still in its infancy, two decades of broader microbiome research and discovery supports a role of the human gut microbiome in the regulation of bone metabolism and pathogenesis of osteoporosis as well as its prevention and treatment. Pre-clinical research has demonstrated biological interactions between the microbiome and bone metabolism. Furthermore, observational studies and randomized clinical trials have indicated that therapeutic manipulation of the microbiota by oral administration of probiotics may influence bone turnover and prevent bone loss in humans. In this paper, we summarize the content, discussion and conclusions of a workshop held by the Osteoporosis and Bone Research Academy of the Royal Osteoporosis Society in October, 2020. We provide a detailed review of the literature examining the relationship between the microbiota and bone health in animal models and in humans, as well as formulating the agenda for key research priorities required to advance this field. We also underscore the potential pitfalls in this research field that should be avoided and provide methodological recommendations to facilitate bridging the gap from promising concept to a potential cause and intervention target for osteoporosis.
|
|
17. |
|
|
18. |
- Harbo, HF, et al.
(author)
-
Two genome-wide linkage disequilibrium screens in Scandinavian multiple sclerosis patients
- 2003
-
In: Journal of Neuroimmunology. - : Elsevier BV. - 1872-8421 .- 0165-5728. ; 143:1-2, s. 101-106
-
Journal article (peer-reviewed)abstract
- We report the first two genome-wide screens for linkage disequilibrium between putative multiple sclerosis (MS) susceptibility genes and genetic markers performed in the genetically homogenous Scandinavian population, using 6000 microsatellite markers and DNA pools of approximately 200 MS cases and 200 controls in each screen. Usable data were achieved from the same 3331 markers in both screens. Nine markers from eight genomic regions (1p33, 3q13, 6p21, 6q14, 7p22, 9p21, 9q21 and Xq22) were identified as potentially associated with MS in both screens. (C) 2003 Elsevier B.V. All rights reserved.
|
|
19. |
|
|
20. |
|
|
21. |
- Hensiek, A E, et al.
(author)
-
Familial effects on the clinical course of multiple sclerosis.
- 2007
-
In: Neurology. - : Ovid Technologies (Wolters Kluwer Health). - 1526-632X .- 0028-3878. ; 68:5, s. 376-83
-
Journal article (peer-reviewed)abstract
- BACKGROUND: Familial factors influence susceptibility to multiple sclerosis (MS) but it is unknown whether there are additional effects on the natural history of the disease. METHOD: We evaluated 1,083 families with > or =2 first-degree relatives with MS for concordance of age at onset, clinical course, and disease severity and investigated transmission patterns of these clinical features in affected parent-child pairs. RESULTS: There is concordance for age at onset for all families (correlation coefficient 0.14; p < 0.001), as well as for affected siblings (correlation coefficient 0.15; p < 0.001), and affected parent-child pairs (correlation coefficient 0.12; p = 0.03) when each is evaluated separately. Concordance for year of onset is present among affected siblings (correlation coefficient 0.18; p < 0.001) but not the parent-child group (correlation coefficient 0.08; p = 0.15). The clinical course is similar between siblings (kappa 0.12; p < 0.001) but not affected parents and their children (kappa -0.04; p = 0.09). This influence on the natural history is present in all clinical subgroups of relapsing-remitting, and primary and secondary progressive MS, reflecting a familial effect on episodic and progressive phases of the disease. There is no concordance for disease severity within any of the considered family groups (correlation coefficients: all families analyzed together, 0.02, p = 0.53; affected sibling group, 0.02, p = 0.61; affected parent-child group, 0.02, p = 0.69). Furthermore, there are no apparent transmission patterns of any of the investigated clinical features in affected parent-child pairs and no evidence for anticipation or effects of genetic loading. CONCLUSION: Familial factors do not significantly affect eventual disease severity. However, they increase the probability of a progressive clinical course, either from onset or after a phase of relapsing remitting disease. The familial effect is more likely to reflect genetic than environmental conditions. The results are relevant for counseling patients and have implications for the design of studies seeking to identify factors that influence the natural history of the disease.
|
|
22. |
|
|
23. |
|
|
24. |
|
|
25. |
|
|