| Literature DB >> 29996823 |
Megan M Campbell1, Jantina de Vries2, Sibonile G Mqulwana3, Michael M Mndini3, Odwa A Ntola3, Deborah Jonker3, Megan Malan3, Adele Pretorius3, Zukiswa Zingela4, Stephanus Van Wyk4, Dan J Stein3, Ezra Susser5.
Abstract
BACKGROUND: Cell line immortalisation is a growing component of African genomics research and biobanking. However, little is known about the factors influencing consent to cell line creation and immortalisation in African research settings. We contribute to addressing this gap by exploring three questions in a sample of Xhosa participants recruited for a South African psychiatric genomics study: First, what proportion of participants consented to cell line storage? Second, what were predictors of this consent? Third, what questions were raised by participants during this consent process?Entities:
Keywords: Cell immortalisation; Consent; Neuropsychiatric genomics; Predictors; Xhosa
Mesh:
Year: 2018 PMID: 29996823 PMCID: PMC6042361 DOI: 10.1186/s12910-018-0313-2
Source DB: PubMed Journal: BMC Med Ethics ISSN: 1472-6939 Impact factor: 2.652
Sample information, prevalence ratios and odds ratios of consent to cell line creation
| Sample information | Categories | N (%) | Consent to cell lines | Odds Ratio | CI: 95% |
|---|---|---|---|---|---|
| Total sample | 1520 (100%) | 648 (42.6%) | |||
| Absence/presence of schizophrenia diagnosis | Controls | 760 (50%) | 340 (44.7%) | 1.210 | 0.959–1.527 |
| Cases | 760 (50%) | 308 (40.5%) | |||
| Sex: | Female | 184 (12.1%) | 84 (45.7%) | 1.166 | 0.822–1.655 |
| Male | 1336 (87.9%) | 564 (42.2%) | |||
| Age: | 40–59 | 532 (35%) | 252 (47.4%) | 1.308* | 1.020-1.676 |
| 20–39 | 988 (65%) | 396 (40.1%) | |||
| Education level: | Secondary (≥Grade 8) | 1130 (74.3%) | 485 (42.9%) | 1.041 | 0.791–1.370 |
| Primary (≤Grade 7) | 390 (25.7%) | 163 (41.8%) | |||
| Recruitment region: | Eastern Cape | 878 (57.8%) | 408 (46.5%) | 1.597** | 1.257-2.027 |
| Western Cape | 642 (42.2%) | 240 (37.4%) | |||
| HIV status | Reactive | 185 (12.2%) | 102 (55.1%) | 1.306 | 0.912–1.871 |
| Non-reactive | 1335 (87.8%) | 546 (40.9%) | |||
| SAX Recruiters | |||||
| A | 308 (20.3%) | 230 (74.7%) | 12.587** | 8.815–17.972 | |
| B | 437 (28.8%) | 229 (52.4%) | 4.802** | 3.530–6.532 | |
| C | 207 (13.6%) | 74 (35.7%) | 2.567** | 1.754–3.757 | |
| D | 130 8.6%) | 29 (22.3%) | 1.199 | 0.739–1.944 | |
| E (reference nurse) | 438 (28.8%) | 86 (19.6%) | |||
*p < 0.05
**p < 0.01
Recruiter statistics for: age, region recruited from and HIV status
| Age | Region | HIV status | ||||
|---|---|---|---|---|---|---|
| Recruiter | 20–39 years | 40–59 years | Eastern Cape | Western Cape | Non-Reactive | Reactive |
| A ( | 193 (63%) | 115 (37%) | 185 (60%) | 123 (40%) | 253 (82%) | 65 (18%) |
| B ( | 283 (65%) | 154 (35%) | 243 (56%) | 194 (44%) | 386 (88%) | 51 (12%) |
| C ( | 151 (73%) | 56 (27%) | 96 (46%) | 111 (54%) | 181 (87%) | 26 (13%) |
| D ( | 103 (79%) | 27 (21%) | 89 (64%) | 41 (36%) | 116 (89%) | 14 (11%) |
| E ( | 258 (59%) | 180 (41%) | 265 (60,5%) | 173 (39,5%) | 399 (91%) | 39 (9%) |