Kooperativer Bibliotheksverbund

In: EMBnet.journal, EMBnet Stichting, Vol. 27 ( 2022-07-07), p. e1011-

Abstract: Proteins have a significant role in all biological processes. The functional properties of proteins rely upon their three-dimensional structures. Over the last twenty years substantial advances in genomic technologies have enhanced our knowledge of the genetics of Alzheimer’s disease. To that end the identification of mutations pathogenicity is still of vital importance. The methodology of the present research work focuses on the structural analysis of proteins related to Alzheimer’s disease and the comparative study to create groups with clear structural similarity and pathogenicity. To achieve that, three-dimensional descriptors (fpfh, rsd and 3dsc) were applied along with supervised machine learning classification methods. In total, 62 APP, 286 PSEN1, 68 PSEN2 and 25 MAPT variants were evaluated in our study.The output of the methodology characterized thirty mutations that were unclear at the point of the data collection.

Type of Medium: Online Resource

ISSN: 2226-6089

URL: Article

DOI: 10.14806/ej.27.0.1011

Language: Unknown

Publisher: EMBnet Stichting

Publication Date: 2022

In: Artificial Intelligence in Medicine, Elsevier BV, Vol. 104 ( 2020-04), p. 101844-

Type of Medium: Online Resource

ISSN: 0933-3657

URL: Article

DOI: 10.1016/j.artmed.2020.101844

Language: English

Publisher: Elsevier BV

Publication Date: 2020

detail.hit.zdb_id: 2001878-2

In: The Journal of Allergy and Clinical Immunology: In Practice, Elsevier BV, Vol. 8, No. 6 ( 2020-06), p. 1972-1979.e8

Type of Medium: Online Resource

ISSN: 2213-2198

URL: Article

DOI: 10.1016/j.jaip.2020.02.018

Language: English

Publisher: Elsevier BV

Publication Date: 2020

In: Blood, American Society of Hematology, Vol. 126, No. 23 ( 2015-12-03), p. 1479-1479

Abstract: B cells residing the marginal zone (MZ) provide a first line of defense against blood borne pathogens, producing the greater part of circulating natural antibodies conferring protection against infection. Dysregulated homeostasis and function of MZ B cells has been implicated in a wide range of B lymphoproliferations, encompassing the distinct MZ lymphomas recognized by the WHO Classification, the related provisional entities and even chronic lymphocytic leukemia (CLL), for which a MZ derivation has been proposed. Here, taking advantage of a large multi-institutional series, we aimed at obtaining insight into the ontogenetic relationship of MZ lymphoproliferations, related entities and CLL through cross-comparison of their B cell receptor immunoglobulin (BcR IG) gene repertoires. Our sequence dataset included 3660 unique IGHV-IGHD-IGHJ gene rearrangement sequences from our collaborative centers and/or public databases derived from: (1) MZ lymphomas: splenic (SMZL), n=379; nodal (NMZL), n=37; extranodal (ENMZL), n=95; (2) provisional entities of postulated MZ origin, including splenic diffuse red pulp lymphoma (SDRL, n=16) and clonal B cell lymphocytosis of MZ origin (CBL-MZ, n=60); (3) persistent polyclonal B cell lymphocytosis (PPBL), n=286 (from 2 cases); (4) MZ cells isolated from six spleen specimens free of neoplastic cells at histological inspection (non-malignant MZ), obtained at surgery for cancer, n=489; (5) autoimmune conditions, n=1243; (6) various types of normal B cells, n=1055. The most pronounced IG gene repertoire skewing was observed in SMZL with the IGHV1-2*04 gene accounting for 26% of cases. Restrictions, though less striking, were also identified in the other MZ lymphomas as well: (i) the IGHV4-34 gene predominated in NMZL (14.3%); and, (ii) the IGHV1-69 gene predominated in ENMZL (14.6%), albeit with significantly different distribution depending on the primary site of involvement, ranging from 38% in salivary ENMZL to 11% in gastric ENMZL to 4% in ocular adnexa ENMZL (p 〈 0.01). The vast majority of MZL cases showed at least some impact of somatic hypermutation (SHM), with the proportion of cases lacking any SHM ranging from 0% in salivary ENMZ to only 13% in SMZL. Following established bioinformatics approaches, we searched for stereotyped BcR IG sequences i.e. IGHV-IGHD-IGHJ gene rearrangements with restricted antigen-binding site sequence motifs. For the purposes of this analysis, the present sequence dataset was cross-compared to a large dataset of 20451 IGHV-IGHD-IGHJ gene rearrangement sequences from CLL patients from the IMGT/CLL-DB. Overall, 6437 different clusters with stereotyped BcR IG sequences were identified in the merged dataset, including from only 2 to more than 350 sequences. Two categories of clusters with stereotyped BcR IG were identified: disease-specific (n=4813) and 'mixed' (n=1624) i.e. comprised of cases with different diagnosis. The great majority of clusters in the former category concerned exclusively CLL and corresponded to well-established CLL stereotyped subsets, while only a small minority concerned exclusively MZ lymphomas, all with a diagnosis of SMZL. Mixed clusters were relatively small in size, with only 4 populated by more than 10 cases; of these, 2 utilized the IGHV1-69 gene, while the remaining 2 utilized the IGHV3-7 and IGHV4-59 gene, respectively. They comprised rearrangements from various entities, including SMZL, ENMZL (gastric, salivary gland, ocular adnexa), CLL, hepatitis C virus-associated diffuse large B cell lymphoma (DLBCL), but also rheumatoid factors and non-malignant spleen MZ cells. Notably, shared (recurrent) amino acid changes introduced by SHM (i.e. the same amino acid replacement at the same position) were identified in each mixed cluster. In conclusion, we document different immunogenetic signatures for MZ lymphomas, with limited overlap both amongst the various distinct and provisional WHO entities but also versus CLL. These findings indicate distinct antigen exposure histories and/or different (micro)environments underlying the ontogeny of MZ lymphomas. That said, the existence of rare public stereotypes raises the intriguing possibility that common, pathogen-triggered, immune-mediated mechanisms, may result in diverse B lymphoproliferations due to targeting versatile progenitor B cells and/or operating in particular microenvironments. Disclosures Ghia: Janssen Pharmaceuticals: Research Funding.

Type of Medium: Online Resource

ISSN: 0006-4971 , 1528-0020

URL: Article

DOI: 10.1182/blood.V126.23.1479.1479

Language: English

Publisher: American Society of Hematology

Publication Date: 2015

detail.hit.zdb_id: 1468538-3

detail.hit.zdb_id: 80069-7

In: BMC Bioinformatics, Springer Science and Business Media LLC, Vol. 19, No. S14 ( 2018-11)

Type of Medium: Online Resource

ISSN: 1471-2105

URL: Article

DOI: 10.1186/s12859-018-2381-1

Language: English

Publisher: Springer Science and Business Media LLC

Publication Date: 2018

detail.hit.zdb_id: 2041484-5

SSG: 12

In: Blood, American Society of Hematology, Vol. 128, No. 22 ( 2016-12-02), p. 4376-4376

Abstract: The existence of stereotyped B cell receptor immunoglobulins (BcR IG) in chronic lymphocytic leukemia (CLL) strongly implicated antigen selection in disease ontogeny. We have previously shown that the stereotyped fraction encompasses ~30% of all CLL and includes multiple subsets with distinct BcR IG configuration and variable size. Eventually, certain major subsets emerged as distinct clinical entities, exemplified by subset #2 (IGHV3-21/IGLV3-21, ~2.5-3% of all CLL, mixed somatic hypermutation (SHM) status) of a particularly aggressive clinical course, thus, sharply contrasting subset #4 (IGHV4-34/IGKV2-30, ~1% of all CLL, mutated IGHV genes, M-CLL), a prototype for indolent disease. Here, taking advantage of a multi-institutional cohort of 21,123 CLL IG rearrangements, almost three times the size of the largest previous study, and the availability of validated, purpose-built immunoinformatics methods, we reappraised BcR IG stereotypy especially focusing on major subsets and the degree of their sequence similarity to related minor subsets. Stereotypy discovery was performed with ARResT/Teiresias, while stereotypy assignment to existing subsets previously deemed as major was performed with ARResT/AssignSubsets (http://bat.infspire.org/arrest/). In the present study, a subset was characterized as major if representing 〉 0.2% of the cohort (i.e. at least 50 cases). Minor subsets closely related to major ones (termed satellite) were identified applying the following criteria: (i) usage of IGHV genes from the same phylogenetic clan; (ii) VH CDR3 length difference ranging from -2 to +2 compared to the respective major subset; (iii) shared VH CDR3 sequence motif; and, (iv) -2 to +2 difference in the offset of the VH CDR3 motif compared to the respective major subset. In total, 7378/21123 (34.9%) IG sequences were grouped into subsets with stereotyped VH CDR3, with the previously characterized 19 major subsets accounting collectively for 2594 sequences (12.3%) of the cohort: of these, 12 included cases with unmutated IGHV genes (U-CLL), 6 concerned M-CLL and 1 (subset #2) included cases with mixed SHM status. Four additional subsets exceeded 50 cases, and, thus, were also considered as 'major'. These results reinforce the notion that not all CLL will end up being stereotyped but rather that a plateau for stereotypy exists at ~1/3 of the cohort. Subset #2 was the largest subset (n=572, 2.7%), while subset #1 (IGHV clan I (IGHV1,5,7 subgroups)/IGKV1(D)-39) was the most frequent subset within U-CLL (n=515, 2.4%) and subset #4 the most common M-CLL subset (n=192, 0.9%), hence displaying remarkable consistency regarding their frequency in all cohorts published since the pioneering studies. Altogether, Teiresias and AssignSubsets gave concordant results for previously identified major subsets, illustrating the validity of our approach. Satellite subsets were sought for individually for each major subset. In general, few satellite subsets were identified, most of which concerned U-CLL major subsets. That notwithstanding, notable cases of satellite subsets were exemplified by major subset #1 and its satellite subset #99 from which it differed only in VH CDR3 length (13 aminoacids in subset #1 versus 14 in subset #99); interestingly, both subsets displayed equally aggressive clinical course. Another example concerned subset #8 (IGHV4-39/IGKV1(D)-39, U-CLL), an aggressive subset with very high risk for Richter's transformation, that, except for a one-aminoacid difference in VH CDR3 length, was otherwise identical to satellite subset #215, also displaying clinical aggressiveness. Overall, our results confirm that major subsets can be robustly identified and are consistent in relative size, hence representing distinct disease subgroups amenable to compartmentalized research with the potential of overcoming the pronounced heterogeneity of CLL. Most major subsets display unique sequence motifs, however satellite subsets exist, especially within U-CLL. Considering ever-increasing evidence that major stereotyped subsets may represent distinct disease subgroups, the existence of satellite subsets reveals a novel aspect of repertoire restriction and has implications for refined molecular classification of CLL. Disclosures Shanafelt: Genentech: Research Funding; GlaxoSmithkKine: Research Funding; Celgene: Research Funding; Janssen: Research Funding; Pharmacyclics: Research Funding; Cephalon: Research Funding; Hospira: Research Funding. Gaidano:Roche: Consultancy, Honoraria, Speakers Bureau; Karyopharm: Consultancy, Honoraria; Morphosys: Consultancy, Honoraria; Gilead: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; Novartis: Consultancy, Honoraria, Speakers Bureau. Niemann:Janssen: Consultancy; Abbvie: Consultancy; Roche: Consultancy; Gilead: Consultancy. Langerak:F. Hofmann-LaRoche, Genentech: Research Funding; InVivoScribe Technologies: Patents & Royalties: Royalties are provided to European Network (EuroClonality). Jaeger:Roche: Honoraria, Research Funding; Celgene: Honoraria, Research Funding. Kater:Celgene: Research Funding; Gilead: Research Funding; Janssen: Consultancy, Research Funding; Roche: Consultancy, Research Funding; Abbvie: Consultancy, Research Funding. Stilgenbauer:Amgen: Consultancy, Honoraria, Other: Travel grants, Research Funding; Gilead: Consultancy, Honoraria, Other: Travel grants , Research Funding; Genentech: Consultancy, Honoraria, Other: Travel grants , Research Funding; Celgene: Consultancy, Honoraria, Other: Travel grants , Research Funding; Boehringer Ingelheim: Consultancy, Honoraria, Other: Travel grants , Research Funding; Genzyme: Consultancy, Honoraria, Other: Travel grants , Research Funding; AbbVie: Consultancy, Honoraria, Other: Travel grants, Research Funding; GSK: Consultancy, Honoraria, Other: Travel grants , Research Funding; Janssen: Consultancy, Honoraria, Other: Travel grants , Research Funding; Mundipharma: Consultancy, Honoraria, Other: Travel grants , Research Funding; Novartis: Consultancy, Honoraria, Other: Travel grants , Research Funding; Pharmacyclics: Consultancy, Honoraria, Other: Travel grants , Research Funding; Hoffmann-La Roche: Consultancy, Honoraria, Other: Travel grants , Research Funding; Sanofi: Consultancy, Honoraria, Other: Travel grants , Research Funding. Hallek:Gilead: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau; F. Hoffmann-LaRoche: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau; Mundipharma: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau; AbbVie: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau; Janssen-Cilag: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau. Rosenquist:Gilead Sciences: Speakers Bureau. Ghia:Gilead: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; Roche: Honoraria, Research Funding; Adaptive: Consultancy; Abbvie: Consultancy, Honoraria. Stamatopoulos:Novartis: Honoraria, Research Funding; Abbvie: Honoraria, Other: Travel expenses; Janssen: Honoraria, Other: Travel expenses, Research Funding; Gilead: Consultancy, Honoraria, Research Funding.

Type of Medium: Online Resource

ISSN: 0006-4971 , 1528-0020

URL: Article

DOI: 10.1182/blood.V128.22.4376.4376

Language: English

Publisher: American Society of Hematology

Publication Date: 2016

detail.hit.zdb_id: 1468538-3

detail.hit.zdb_id: 80069-7

In: The Journal of Pathology, Wiley, Vol. 247, No. 4 ( 2019-04), p. 416-421

Abstract: The B cell receptor immunoglobulin (Ig) gene repertoires of marginal zone (MZ) lymphoproliferations were analyzed in order to obtain insight into their ontogenetic relationships. Our cohort included cases with MZ lymphomas ( n = 488), i.e. splenic (SMZL), nodal (NMZL) and extranodal (ENMZL), as well as provisional entities ( n = 76), according to the WHO classification. The most striking Ig gene repertoire skewing was observed in SMZL. However, restrictions were also identified in all other MZ lymphomas studied, particularly ENMZL, with significantly different Ig gene distributions depending on the primary site of involvement. Cross‐entity comparisons of the MZ Ig sequence dataset with a large dataset of Ig sequences (MZ‐related or not; n = 65 837) revealed four major clusters of cases sharing homologous (‘public’) heavy variable complementarity‐determining region 3. These clusters included rearrangements from SMZL, ENMZL (gastric, salivary gland, ocular adnexa), chronic lymphocytic leukemia, but also rheumatoid factors and non‐malignant splenic MZ cells. In conclusion, different MZ lymphomas display biased immunogenetic signatures indicating distinct antigen exposure histories. The existence of rare public stereotypes raises the intriguing possibility that common, pathogen‐triggered, immune‐mediated mechanisms may result in diverse B lymphoproliferations due to targeting versatile progenitor B cells and/or operating in particular microenvironments. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Type of Medium: Online Resource

ISSN: 0022-3417 , 1096-9896

URL: Issue

URL: Article

DOI: 10.1002/path.2019.247.issue-4

DOI: 10.1002/path.5209

Language: English

Publisher: Wiley

Publication Date: 2019

detail.hit.zdb_id: 1475280-3

In: BMC Infectious Diseases, Springer Science and Business Media LLC, Vol. 21, No. S2 ( 2021-09)

Abstract: The HIV pandemic impacts the lives of millions and despite the global coordinated response, innovative actions are still needed to end it. A major challenge is the added burden of coinfections such as viral hepatitis, tuberculosis and various sexually transmitted infections in terms of prevention, treatment and increased morbidity in individuals with HIV infection. A need for combination prevention strategies, tailored to high-risk key populations arises and technology-based interventions can be a valuable asset. The COVID-19 pandemic challenged the delivery of existing services and added stress to existing public health and clinical structures but also highlighted the potential of exploiting technical solutions for interventions regarding infectious diseases. In this paper we report the design process, results and evaluation findings from the pilots of ‘RiskRadar’—a web and mobile application aiming to support combination prevention, testing and linkage to care for HIV, viral hepatitis, various sexually transmitted infections and tuberculosis. Methods RiskRadar was developed for the INTEGRATE Joint Action’s aim to improve, adapt and pilot innovative digital tools for combination prevention. RiskRadar was designed iteratively using informed end-user-oriented approaches. Emphasis was placed on the Risk Calculator that enables users to assess their risk of exposure to one or more of the four disease areas, make informed decisions to seek testing or care and adjust their behaviours ultimately aiming to harm/risk reduction. RiskRadar has been piloted in three countries, namely Croatia, Italy and Lithuania. Results RiskRadar has been used 1347 times across all platforms so far. More than 90% of users have found RiskRadar useful and would use it again, especially the Risk Calculator component. Almost 49.25% are men and 29.85% are in the age group of 25–34. The application has scored 5.2/7 in the User Experience Questionnaire, where it is mainly described as “supportive” and “easy-to-use”. The qualitative evaluation of RiskRadar also yielded positive feedback. Conclusions Pilot results demonstrate above average satisfaction with RiskRadar and high user-reported usability scores, supporting the idea that technical interventions could significantly support combination prevention actions on Sexually Transmitted Infections.

Type of Medium: Online Resource

ISSN: 1471-2334

URL: Article

DOI: 10.1186/s12879-021-06501-0

Language: English

Publisher: Springer Science and Business Media LLC

Publication Date: 2021

detail.hit.zdb_id: 2041550-3