Study samples and populations
Samples from cohorts enrolled at 3 sites in Uganda were utilized, that is, Nagongera Sub-county in Tororo District, a rural area in south-eastern Uganda with historically high malaria transmission intensity; Walukuba Sub-county in Jinja District, a peri-urban area near the city of Jinja in south-central Uganda with historically moderate malaria transmission intensity; and Kihihi Sub-county in Kanungu District, a rural area in south-western Uganda with historically low malaria transmission intensity.
The total population of Nagongera sub-county, Tororo district was 37,500. All participants at this site were recruited within Nagongera Health Center IV which is the largest public health facility in the sub-county and treated an average of 2,044 patients per month. Walukuba sub-county, Jinja district has an estimated population of 31,900. Study participants from Walukuba sub-county were recruited within Walukuba health centre IV, the largest public health facility in the sub-county and treated an average of 3,198 patients per month. Kihihi is a rural sub-county in Kanungu district with an estimated population of 55,700. Study participants were recruited within Kihihi health centre IV which is the largest healthcare facility in Kihihi sub-county, a public health facility that treated an average of 1,945 patients per month.
To establish these cohorts, all households within the 3 sites were enumerated and mapped, and randomly selected 100 households that included at least one resident 6 months to 10 years of age were enrolled and followed from August 2011 to September 2013, as previously described (23). All the participants enrolled in these cohorts provided thick blood smears and a blood sample for genetic analysis. For this study, all participants whose parents consented to future use of their samples were considered. No a priori power calculation was performed.
Sample collection and DNA purification
Blood samples from previous studies (24) were collected into EDTA tubes, and human genomic DNA was purified from buffy coats using QIAamp DNA Mini Kits (Qiagen), following manufacturer’s instructions using kit inserts with minor modifications. For each sample 300 μl of buffy coat was mixed with 20 μl of kit protease enzyme solution and then 200 μl of lysis buffer, the mixture was vortexed for 15 seconds and incubated at 56°C for 10 minutes, and then 200 μl of absolute ethanol was added. The mixture was vortexed briefly and transferred to a QIAamp column, and the column was spun for 1 minute at 8000 rpm. The column was then washed twice with kit wash buffer, and DNA was eluted by incubating with 80 μl of kit elution buffer at room temperature for 5 minutes followed by centrifugation at 8,000 rpm for 5 minutes. The DNA concentration was determined using a Qubit fluorimeter (Life Technologies, Carlsbad, CA), and the isolated DNA was stored at −20°C.
Preparation of DNA for multiplex qPCR
To prepare human genomic DNA for KIR and HLA-C genotyping as well as KIR copy number identification, 10 ng samples of genomic DNA (2.5 µl of 4 ng/µl) were aliquoted into 384-well plates using the Hydra 96 micro dispenser (Art Robbins, San Jose, CA) (25). The DNA was air dried in the plates for subsequent multiplex quantitative PCR assays. Molecular grade water was used in all reactions.
KIR genotyping by high throughput multiplex real-time qPCR
Two pairs of primers were used for each gene, as previously described (26). Additional KIR primers were designed using sequence information from the immuno polymorphism database-KIR (IPD-KIR) database (release 2.4.0) to detect rare alleles of KIR2DS5 and KIR2DL3 (KIR2DS5, 2DS5rev2: TCC AGA GGG TCA CTG GGA and KIR2DL3, 2DL3rev3: AGA CTC TTG GTC CAT TAC CG) (27). Samples were genotyped for copy number by multiplex quantitative PCR for all the KIR genes (KIR2DL1, 2DL2, 2DL3, 2DL4, 2DL5, 2DS1, 2DS2, 2DS3, 2DS4, 2DS5, 2DP1, 3DP1, 3DL1, 3DL2, 3DL3, and 3DS1) (25). Reactions were carried out in quadruplicate to ensure accuracy of the copy number scoring. Two controls with known copy number and one non-template control were included in each run. Two assays for both 3DL1 and 3DL2 genes that target different exons of the genes were included to identify known fusion genes (28), which are carried on a truncated haplotype (with 2DS4 completely deleted) seen in individuals of African descent. There is a drop in copy number for exon 9 of 3DL1 and exon 4 of 3DL2 (i.e. discordance between the exon 4 and exon 9 copy numbers in the same gene) when the fusion gene is present. Assays for 2DS4 variants, 2DS4DEL (a 22-bp deletion in exon 5 that causes a frameshift mutation) and 2DS4WT (full-length gene) were also included.
HLA-C genotyping by high throughput multiplex real-time quantitative PCR
A high throughput real-time qPCR for genotyping HLA-C allotypes was developed. For every reaction, KAPA SYBR buffer (5µl), forward primer (1µl), reverse primer (1µl) and water (4µl) were added to dried DNA in the 384 well plates. HLA-C1 PCR conditions were: denaturation at 95˚C for 3 minutes, 5 cycles of 95˚C for 3 seconds and 72˚C for 30 seconds, followed by 35 cycles of 95˚C for 3 seconds and 70˚C for 30 seconds, dissociation at 60˚C for 1 second, and finally 95˚C. HLA-C2 PCR conditions were: denaturation at 95˚C for 3 minutes, 5 cycles of 95˚C for 3 seconds and 72˚C for 45 seconds, followed by 40 cycles of 95˚C for 3 seconds and 70˚C for 45 seconds, dissociation at 60˚C for 1 second, and finally 95˚C. In each HLA-C allotype, primers were used at 5µM concentrations. Primer combinations for C1 and C2 were: C1 = C1Fa and C1Fb with C1R, and C2 = C2F with C2R respectively (Table 1). This method was validated against a large range of samples, the HLA Reference Panel from Coriell with known HLA-C allotypes and in families. The sequences for each of the primers used are shown in Table 1.
KIR and HLA-C genotypes analysis
KIR genotypes were defined following the recommendations from the 2011 KIR workshop that was held at Tammsvik, Stockholm, Sweden (29). Briefly, the centromeric A region (cenA) was defined by the presence of KIR2DL3 and KIR2DL1 and absence of any A haplotype gene, the centromeric B (cenB) region was defined by presence of any centromeric B haplotype gene (KIR2DS2 and/or KIR2DL2, and/or 2DL5B and/or centromeric 2DS3/5). The telomeric A (telA) region was defined by KIR3DL1 and KIR2DS4 and absence of any A haplotype gene, and the telomeric B (telB) region was defined by presence of any centromeric B haplotype gene (KIR3DS1 and/or KIR2DS1 and or 2DL5B and/or telomeric 2DS5) (Fig. 1). The KIR and HLA-C genotypes were ascertained according to the Allele Frequency Net Database (http://www.allele frequencies.net).
KIR Copy number determination by multiplex quantitative PCR
Copy numbers for all KIR genes (KIR2DL1–5, 2DS1–5, 2DS4 (separate assays for the gene, wild-type variant [2DS4WT], and deletion variant [2DS4DEL]), 2DP1, 3DP1, 3DL1-3 and 3DS1) were determined using a Roche Light Cycler 480. Copy numbers were measured by relative quantification analysis of the target KIR gene and reference gene (signal transducer and activator of transcription 6; STAT 6) using the comparative Cq method (25, 30). Cq value is the qPCR cycle at which fluorescence from amplification exceeds the background fluorescence (also referred to as threshold cycle, Ct). The ΔΔCq was used to calculate KIR copy number. The first ΔCq was calculated by the cycle threshold difference between the target and reference assay of the same sample. The second ΔCq was calculated by the difference of ΔCq values from a test sample and a calibrator sample with known copy number of the target. Two controls with known copy number and one non-template control were included in each run. COPYCALLER software from Applied Biosystems (Foster City, CA) was used to score KIR copy numbers. When the Cq of the reference gene was greater than 32 or a data point was more than 4 SD from the mean ΔCq of four replicates, the reaction was not analysed. KIR copy number frequencies were calculated for all the samples.
Data across the 3 sites was described using frequencies and percentages for categorical variables. Frequencies of KIR genes, KIR genotypes and HLA-C allotypes were calculated by direct counting. Differences in the distribution of KIR and HLA-C genetic variants within the three populations were compared by Chi-square and Mid-P exact tests. A p-value < 0.05 was considered significant.