Table 1.
Population characteristics and APOL1 allele and genotype frequencies in the Africa Wits–International Network for the Demographic Evaluation of Populations and Their Health Partnership for Genomic Studies
| Variablea | Africa Wits–International Network for the Demographic Evaluation of Populations and Their Health Partnership for Genomic Studies Site | ||||||
|---|---|---|---|---|---|---|---|
| South Africa | East Africa | West Africa | Overall | ||||
| Agincourt, Rural | Soweto, Urban | Dikgale, Rural | Nairobi, Urban | Nanoro, Rural | Navrongo, Rural | All Sites | |
| Sample size, N | 2253 | 1775 | 1143 | 1771 | 1983 | 1844 | 10,769 |
| Clinical phenotype | |||||||
| Age, yr | 58 (11) | 49 (6) | 52 (8) | 49 (6) | 50 (6) | 51 (6) | 52 (8) |
| Men, N (%) | 938 (42) | 922 (52) | 361 (32) | 804 (45) | 1009 (51) | 842 (46) | 4876 (45) |
| Women, N (%) | 1315 (58) | 853 (48) | 782 (68) | 967 (55) | 974 (49) | 1002 (64) | 5893 (55) |
| Height, m | 1.65 (0.85) | 1.65 (0.88) | 1.62 (0.84) | 1.64 (0.87) | 1.68 (0.87) | 1.62 (0.86) | 1.65 (0.89) |
| Weight, kg | 74 (17) | 78 (19) | 72 (20) | 68 (14) | 59 (12) | 57 (10) | 68 (17) |
| BMI, kg/m2b | 27.2 (6.7) | 28.9 (7.7) | 27.8 (8.2) | 25.4 (5.7) | 21.0 (3.5) | 21.6 (3.6) | 25.1 (6.7) |
| Diabetes mellitus, N (%)c | 194/2214 (9) | 167/1770 (9) | 113/1136 (10) | 124/1755 (7) | 72/1973 (4) | 25/1794 (1) | 695/10,642 (7) |
| Hypertension, N (%) | 1265/2253 (56) | 949/1775 (54) | 515/1143 (45) | 486/1771 (27) | 322/1983 (16) | 455/1844 (25) | 3992/10,769 (37) |
| HIV infection, N (%)d | 602/2251 (27) | 253/1207 (21) | 224/1124 (20) | 216/1561 (14) | 8/1983 (0.4) | 15/1844 (0.8) | 1318/9970 (13) |
| Biomarkers of kidney function, median (IQR) | |||||||
| Serum creatinine, mg/dle | 0.77 (0.22) | 0.79 (0.22) | 0.78 (0.24) | 0.75 (0.21) | 0.72 (0.21) | 0.75 (0.21) | 0.82 (0.2) |
| eGFR, ml/min per 1.73 m2e,f | 92 (21) | 100 (23) | 95 (25) | 102 (17) | 104 (13) | 100 (16) | 100 (20) |
| Urine albumin, mg/gg | 4 (10) | 1 (6) | 3 (8) | 4 (8) | 2 (3) | 1 (2) | 2 (6) |
| Biomarkers of kidney disease,h N (%) | |||||||
| Low eGFRi | 114/2197 (5.2) | 53/1724 (3.1) | 36/1140 (3.2) | 55/1768 (3.1) | 45/1970 (2.3) | 44/1843 (2.4) | 347/10,642 (3.3) |
| Albuminuriag,j | 258/1789 (14) | 107/857 (13) | 115/1024 (11) | 184/1599 (12) | 114/1913 (6) | 114/1701 (7) | 892/8883 (10) |
| Composite end pointk | 295/1740 (17) | 120/856 (14) | 142/1021 (14) | 222/1596 (14) | 144/1902 (8) | 151/1700 (9) | 1074/8815 (12) |
| APOL1 allele distributions, N (%) | |||||||
| G0 allele | 2999 (67) | 2666 (75) | 1730 (76) | 3108 (88) | 3098 (78) | 2793 (76) | 16,394 (76) |
| G1 allele | 437 (10) | 355 (10) | 167 (7) | 177 (5) | 500 (13) | 437 (12) | 2073 (10) |
| G2 allele | 1070 (24) | 529 (15) | 389 (17) | 257 (7) | 368 (9) | 458 (12) | 3071 (14) |
| APOL1 genotype distributions, N (%) | |||||||
| 0 risk alleles (G0/G0) | 997 (44)l | 1009 (57)l | 658 (58)l | 1360 (77)l | 1210 (61)l | 1041 (57)l | 6275 (58)l |
| 1 risk allele | 1005 (45)l | 648 (37)l | 414 (36)l | 388 (22)l | 678 (34)l | 711 (39)l | 3844 (36)l |
| G0/G1 | 300 (13) | 266 (15) | 119 (10) | 157 (9) | 393 (20) | 349 (19) | 1584 (15) |
| G0/G2 | 705 (31) | 382 (22) | 295 (26) | 231 (13) | 285 (14) | 362 (20) | 2260 (21) |
| 2 risk alleles | 251 (11)l | 118 (7)l | 71 (6)l | 23 (1)l | 95 (5)l | 92 (5)l | 650 (6)l |
| G1/G1 | 14 (0.6) | 16 (0.9) | 5 (0.4) | 4 (0.2) | 28 (1.4) | 17 (0.9) | 84 (0.8) |
| G1/G2 | 109 (5) | 57 (3) | 38 (3) | 12 (0.7) | 51 (3) | 54 (3) | 321 (3) |
| G2/G2 | 128 (6) | 45 (3) | 28 (3) | 7 (0.4) | 16 (0.8) | 21 (1) | 245 (2) |
BMI, body mass index; IQR, interquartile range.
All data are reported as mean (SD) unless stated otherwise. Categories are reported as number (N) and percentage; percentages may sum to ±100 from rounding up.
BMI missing data overall n=456 (4%): 453 of 456 Agincourt, two of 456 Soweto, and one of 456 Nanoro.
Diabetes mellitus missing data overall n=127 (1%): 50 of 127 Navrongo, 39 of 127 Agincourt, 16 of 127 Nairobi, ten of 127 Nanoro, seven of 127 Dikgale, and five of 127 Soweto.
HIV infection missing data overall n=799 (7%): 568 of 799 Soweto, 210 of 799 Nairobi, 19 of 799 Dikgale, and two of 799 Agincourt.
Serum creatinine eGFR missing data overall n=239 (2%): 91 of 239 Agincourt, 63 of 239 Soweto, 31 of 239 Nanoro, 22 of 239 Navrongo, 21 of 239 Nairobi, and 11 of 239 Dikgale.
eGFR is calculated using the Chronic Kidney Disease Epidemiology Collaboration (creatinine) equation 2009 without adjusting for the African American coefficient.
Urine albumin and albuminuria missing data overall n=1886 (18%): 918 of 1886 Soweto, 464 of 1886 Agincourt, 172 of 1886 Nairobi, 143 of 1886 Navrongo, 119 of 1886 Dikgale, and 70 of 1886 Nanoro.
For biomarkers of kidney disease, repeat measures for those with albuminuria or low eGFR were not performed, preventing confirmation of CKD. The category “Biomarkers of kidney disease” was used to define these measures on a single screening.
Low eGFR is eGFR <60 ml/min per 1.73 m2 calculated using the Chronic Kidney Disease Epidemiology Collaboration (creatinine) equation 2009 without adjusting for the African American coefficient.
Albuminuria is random spot urine albumin-creatinine ratio >30 mg/g.
The composite end point is low eGFR and/or albuminuria.
Corresponds at main section and in genotype at the total of individual with zero risk allele, one risk allele, and two risk alleles.