The effects of ethnicity, socioeconomic status and autoantibodies on clinical outcome in patients with systemic lupus erythematosus
Bibliographic record
Abstract
Non-biological factors are impoftant determinants of health ancl known to impact on the olltcome of many chronic conclitions.Specifically, socioeconornic status (SES), which is affectecl by multiple factols including education level, income, and type of occt4ration can affect health related behaviors, attitudes to health care, and potentially affect access to or compliance with health care interveutions.Poor SES has aclverse effects on chronic conclitions such as diabetes ancl there is eviclence to suggest it may also aclversely affect SLE outcome.Thus, several factors are potentially imporlant in determining disease severity ancl outcome as reflectecl by measules of disease activity, encl organ damage and mortality.This thesis u,ill review the published literature addressing the roles of ethnicity, socioeconomic status and autoantibody profìle, in particular antibodies to extractable nuclear antigen, in detelrnining morbiclity and mortality in SLE.In addition, a systematic review of the literature studying ENA associations with clinical features will be presented as well as a f-omral analysis of the roles of ethnicity, socioeconomic statLrs and antiboclies to extractable nuclear antigens on clinical outcomes in the Manitoba Lnpns population. CHAPTEII2The role of genetics in SLE, Ethnic dilïelences in the plevalence and sevelity of SLE have been leportecl.African Americans, Hispanics, Afro-Caribbeans, Asian Orientals and Native North Americar.lIndians (First Nations) have all been shown to have a higher incidence and severity of SLE compared to Caucasians of the same areas.In contrast, SLE is rare in West ancl Central Africa.(ll 12) (13;1a).This variability may relate to differences in genetic backgror"urd or envirorunental and cultural influences.In the case of lupus in patients of Afi'ican ancestry, the increasing prevalence gradient of lupus in populations fi'om Africa to Er.rrope or North America suggests that a potential interaction between genetic background(s) or the admixtul'e of genetic backgrounds and elrvirorllental int'iuences may contribute to the development of SLE (15;16).SimiÌarly, Hispanic populations from the USA, Latin America, ancl Mexico have also shown differences in SLE sevelity, autoantibody procluction and genetic background(17-22).Many of these findings have been demonstrated thlough a multicenter collabolative study: the Lupr:s in Minority Populations Natule velslrs Nuture (LUMINA) ancl many of the LUMINA findings have been supported by a recent large rnulticenter coholt from Latin Amelica: the Grr-rpo Latinoanericano de Estudio clel Lupus (GLADEL) study ( 23).Comparisons of Hispanics from continental USA (Texas) and the island of Puerto Rico analyzecl by the LUMINA study have shown higher disease activity, nlore orgall involvement, higher frequency of anti-clsDNA autoantibodies, ancl more damage accrual in patients from Texas(21).Althougli these diffelellces wele mecliated by several factors including genetics, environmental factors and social factors, genetics appeared to be the rlost imporlant.Hispanics have mixtures of Western European Qnainly Spanish), African and Amerinclian ancestry although the influences of each ancestry vary between Flispariic subpopulations.Hispanics from Texas are believed to have a higher proportion of Amerindian ancestry, primarily Aztecs and Mayas, rvhile Hispanics from Puerto Rico may have Tainos background.The authors of this work suggest that the greater severity of lupus in Texan l{ispanics may be relateci in part, to Amerindian genes.Native Americans (First Nations) share genetic ancestry with Asian-Orientals.Similar to Asian Orientals, several Native American grollps have been shou'n to have an increased incidence and prevalence of lnpus compared to Caucasians.Disease severity varies in groups with high disease prevalence with some Native Amelican (Filst Nations) gror,4rs having relatively rnilcl disease and others quite severe disease witli high frequencies of serious end organ involvemetf (reviewed in (13)).Specific genetic associations in lupus have been studied by determining the associations o1' individual gene alleles with disease and by genetic linkage studies that associate chrornosolnal regions witli disease.Like other autoimrnurìe conditions.rnultiple genes are likely requirecl to develop SLE.Potential candiclate genes would likely contribute to clisease susceptibility ancl the incluction of autoimnunity, immune specifìcity, or the inclividual host response.Several lupus-associated genes have been identihed that relate to histocompatibility FILA ìraplotypes, complement components ancl cytokines, and iurmunoglobulin receptol's.In addition, specifrc fèatures of SLE rnay have genetic preclispositions.Interpretation of genetic associations in lnpns is clifficult in many cases due to concerlls of linkage disequilibrium in which thele is close association of the marl
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".