Molecular characterisation of sickle cell disease and classification of major haplotypes associated with the β-globin cluster (HBB gene) by means of SNP marker sequencing in a group of samples from Bolívar, Colombia

Figures & data

Table 1. Age and sex data of the population groups analysed.

Population group	General data	Mean ± SD
CALAMAR, BOLÍVAR (2022, n = 25)	Age (years)	26.9 ± 12.3
	Female gender (%)	84
	Male gender (%)	16
MOMPOX, BOLÍVAR (2022, n = 23)	Age (years)	29.4 ± 16.9
	Female gender (%)	78.26
	Male gender (%)	21.73
“CARTAGENA DE INDIAS”, BOLÍVAR (2022, n = 130)	Age (years)	44.2 ± 15.4
	Female gender (%)	33.84
	Male gender (%)	66.15
MUNICIPALITIES OF THE “CANAL DEL DIQUE”, BOLÍVAR (2010, n = 12): Arroyohondo (2), Calamar (3), Marialabaja (1), Turbana (3), Turbaco (3)	Age (years)	15.8 ± 7.5
	Female gender (%)	41.66
	Male gender (%)	58.33
BOGOTÁ, D.C. [Newborns^a, (n = 4)]	Age (months)	2.0 ± 0.8
	Female gender (%)	N/A
	Male gender (%)	N/A
BOGOTÁ, D.C. [Controls Genetics Lab. (n = 2)]	Age (years)	50.5 ± 7.8
	Female gender (%)	50
	Male gender (%)	50

^a Newborns in Bogotá Clinics (only the mother’s name is known). These samples corresponded to blood contained in filter paper, from Pregen, Bogotá (Abnormal haemoglobins).

This table does not show data for Palenque de San Basilio, Pacific and Providencia Island, since they are not available.

Table 2. Haematological results Calamar (n = 24), Haemoglobin S (n = 25).

Parameters	Mean ± SD^a	Reference values^a
HBG (g/dL)	11.67 ± 1.67	Ref. 11.0–16.0
HCT (%)	35.78 ± 4.76	Ref. 35.0–50.0
MCV (fL)	81.59 ± 9.63	Ref. 80.0–100.0
MCHC (g/dL)	32.59 ± 1.58	Ref. 32.0–36.0
Leukocytes–WBC (10^3/uL)	7.96 ± 2.77	Ref. 4.00–10.00
Platelets–PLT (10^9/L)	325.96 ± 97.65	Ref. 150–450
Reticulocytes (%)	1.88 ± 1.96	Ref. Children: 0.2–4% Ref. Adults: 0.2–2%
HbS (%)^b	9.11 ± 16.09

^a Reference values and data obtained from the “LAB. SIS DIAGNOSTICOS”, Bocagrande Headquarters (Cartagena).

^b Data from the Hb Chromatogram (Pregen, Bogotá, D.C.).

Table 3. Haematological results Mompox (n = 23).

Parameters	Mean ± SD	Reference values^a
HBG (g/dL)	12.64 ± 1.19	Ref. 11–16.5
HCT (%)	39.19 ± 3.06	Ref. 35–42
MCV	85.27 ± 3.35	Ref. 80–97 um^3
MCHC (g/dL)	32.24 ± 1.18	Ref. 31–38
Leukocytes – WBC	4813.04 ± 1648.77	Ref. 5000–10,000/mm^3
Platelets – PLT	268,608.70 ± 69113.04	Ref. 150000–450,000/mm^3
Reticulocytes (%)	0.59 ± 0.11	Ref. Adults: 0.5–1.5% Ref. Children: 2.5–6.5%

^a Reference values and data obtained from the “LAB. BIOCLINICO LUIS CARLOS ANDRADE”, Sta. Lucía Headquarters (Cartagena).

Table 4. Haematological results control genetics lab^b.

Parameters	Data	Reference Values^a
HBG (g/dL)	13.5	Ref. 11–18
HCT (%)	39.5	Ref. 32–43
MCV (fL)	84.2	Ref. 79–101
MCHC (g/dL)	34.2	Ref. 31–37
Leukocytes – WBC (10^3/uL)	6.08	Ref. 4–10
Platelets – PLT (10^3/uL)	353	Ref. 130–450
Reticulocytes (%)	—	—

^a Reference values and data obtained from the CLINIC LAB. – “CLINICA VIP”, International Medicine Centre, Bogotá, DC.

^b (MDM, n = 1 from Bogotá).

Table 5. Description of oligonucleotides designed and selected for amplification (PCR) and Sanger’s Sequencing^a.

No.	Primer	Short name	Sequence (5′ -> 3′)	Length (bp)	Product Size (bp) Primer pair	Annealing T°C
1	Forward	p334-F	AGAAGTCTGCCGTTACTGCC	20	232	58.2
2	Reverse	p334-R	CTGTCTCCACATGCCCAGTT	20
3	Forward	p857-F	TGTCCTTTCCTTGATGGACCC	21	215	60.7
4	Reverse	p857-R	GACCTAAACTGAGGAACCTTTGG	23
5	Forward	p466-F	CCATCTCTCCCATTCTCCTTTTCC	24	297	58.8
6	Reverse	p466-R	TCCCACTGTGGACTACTTGC	20
7	Forward	p105-F	CCCAGGAGCTGTTGAGATGAAA	22	244	60.8
8	Reverse	p105-R	CAACATACAGGGTTCATGGTGG	22
9	Forward	p556-F	GCAACTCTCACCATTATGGGCT	22	213	60.3
10	Reverse	p556-R	TGACTGGGGACTTATCCTATCC	22

^a Primers designed and standardised by M.D.M. during her Post-Doc at Human Genetics Lab., U. Sabana (2022), taking into account what was reported by Shaikho et al. (2017), Shriner & Rotimi (2018), and Adekile et al. (2021). Primers were synthesised in Macrogen (Korea) through CorpoGen Bogotá.

Figure 1. Multiple Compared Graph of Haemoglobin (Hb) frequencies obtained for communities of Bolívar, Colombia. (A) Frequencies of Hb Types obtained for Calamar group from Hb Chromatograms; (B) Frequencies of Hb Types obtained for Cartagena (2022) from Hb Chromatograms in this work; (C) Frequencies of Hb Types obtained for Calamar group with data verified at the sequencing level (SNP rs334) in the present study; (D) Frequencies of Hb Types obtained for the group of municipalities of the “Canal del Dique” from sequencing data (SNP rs334) in the present research; (E) Frequencies of Hb Types obtained for Palenque de San Basilio (SBP) from sequencing data (SNP rs334) in the present work. The population showed in Figure 1(A,C) is the same (Calamar), but with different analyses.

Figure 2. Frequencies of the Glucose 6 Phosphate Dehydrogenase (G6PD) test for Calamar, Bolívar in this study.

Table 6. Frequency of structural Haemoglobinopathies found in samples from Colombia (n = 101), based on the SNP rs334 through Sanger’s Sequencing^a.

Municipality/City/Region	Frequency of structural Haemoglobinopathies Ref. Seq.: Accession No. NC_000011.10 – NCBI (np. 5,227,002)
Calamar (22), Palenque de San Basilio (7), Mompox (23), Pacific (6), Bogotá-Pregen (1), Bogotá – Controls Genetics Lab. (2).	HbA (Normal or not affected)	61 (60.39%)
Calamar (4), Arroyohondo (1), María la Baja (1), Turbana (3), Turbaco (2), Cartagena (2), Palenque de San Basilio (8), Pacífico (6), Providencia Island (5), Bogotá-Pregen (3).	Heterozygous HbAS	35 (34.65%)
Calamar (1), Palenque de San Basilio (2).	Homozygous HbSS	3 (2.97%)
Arroyohondo (1), Turbaco (1).	Heterozygous HbAC	2 (1.98%)

^aRelate to Table 1 and Table S4.

Table 7. Results of classical haplotypes associated with the β-globin cluster.

No.	Samples/Individuals	Origin	SNPs to define haplotypes by Sanger’s sequencing				RESULTING CLASSICAL HAPLOTYPE (4 SNPs)
			rs3834466 * np. 5,270,334	rs28440105 np. 5,248,569	rs10128556 np. 5,242,453	rs968857 np. 5,239,228
	Gene		Ε (HBE1)	Aɣ (HBG1)	Ψβ (HBBP1)	5’ δ (HBD)
–	Ref. Seq. (Accession No. NC_000011.10 - NCBI)		T	A	C	T	CAM
1	CAL 12	Calamar	T	C	C	T	BEN
2	CAL 9		T	C	C	C	CAR
3	CAL4		T	C	C	T	BEN
4	CAL 18		T	C	C	T	BEN
5	CAL 14		T	C	T	T	SEN
6	CAL 17		T	C	C	C	CAR
7	CAL 11		T	C	C	C	CAR
8	Pregen 1 (155114)	Newborns -Bogotá Clinic	T	C	C	C	CAR
9	Pregen 3 (155199)		T	C	C	C	CAR
10	Pregen 4 (156436)		T	C	C	T	BEN
11	JCM	Bogotá, D.C.	TT	C	C	C	ATP-I*
12	SBP-179	Palenque de San Basilio	T	C	C	C	CAR
13	SBP-272		T	C	C	T	BEN
14	SBP-279		T	A	C	T	CAM
15	SBP-285		T	C	C	C	CAR
16	SBP-313		T	C	C	T	BEN
17	44	Arroyohondo	T	C	C	C	CAR
18	85		T	C	C	T	BEN
19	113	Calamar	T	C	C	C	CAR
20	308	Turbana	T	C	C	T	BEN
21	324		T	A	C	T	CAM
22	351		T	C	C	C	CAR
23	362	Turbaco	T	C	C	C	CAR
24	399	Cartagena	T	C	C	C	CAR
25	409		T	C	C	C	CAR
26	MDM	Bogotá, D.C.	TT	C	C	C	ATP-I*
Total Sequences analysed by 4 SNPs			84	77	84	66	311

*T = 1, TT= 2 (DupT, according to Adekile et al. (2021).

Samples No. 17–25 correspond to municipalities of the “Canal del Dique”, Bolívar (2010). Seven (7) HbA or unaffected individuals were considered.

Figure 3. Classical Haplotype frequencies for individuals of Calamar, Bogotá-Pregen, Palenque de San Basilio, “Canal del Dique” and two controls, from four (4) SNPs (Table 7), in this work.

Table 8. Comparison of classical haplotypes found in eight (8) Studies from the Americas including our study.

Haplotype	U.S. (Haplotypes were inferred in silico) (Cruz et al. 2019)	Cuba (PCR-RFLPs) (Muniz et al. 1995)	Panamá (PCR-RFLPs) (Rusanova et al. 2011)	Colombia Medellín (PCR-RFLPs) (Cuéllar-Ambrosi et al. 2000)	Colombia Montería & Cartagena (PCR-RFLPs) (Fong et al. 2013)	Colombia This study in six communities of Bolívar, and Bogotá (PCR and Sanger’s Sequencing)	Venezuela Aragua State (PCR-RFLPs) (Moreno et al. 2002)	Brazil Ribeirão Preto, State of São Paulo (PCR-RFLPs) (Figueiredo et al. 1994)
N	N = 1,994 (1,822 from 1,000 Genomes repository)	N = 198	N = 100	N = 92	N = 98	N = 26^a	N = 90	N = 67
CAR	10.0%	41.0%	51.0%	55.5%	33.0%	50.0%	43.3%	73.0%
BEN	63.3%	51.0%	30.0%	34.8%	29.0%	30.76%	51.1%	25.5%
CAM	8.3%	0.0%	4.0%	5.4%	4.0%	7.69%	0.0%	0.0%
SEN	6.7%	8.0%	8.5%	4.3%	6.0%	3.84%	3.3%	1.5%
AI	0.0%	0.0%	1.0%	0.0%	1.0%	0.0%	2.2%	0.0%
Atypical	11.7%	0.0%	5.0%	0.0%	∼28%	7.69%^a	0.0%	0.0%

^aN = 26 (21 Bolívar, 5 Bogotá), Atypical 7.69%: Bogotá, D.C (Table 7).

Figure 4. Phylogenetic network of classical haplotypes identified in this study built using Network v.10.2.0.0 (Median joining network). Representation of the haplotype’s relationship based on sequence data from Table 7. The SNPs names are shown in red, abbreviated version (last three numbers, Tables 5 and 7). The central node is CAR haplotype, and the secondary node is BEN haplotype, from the latter SEN and CAM are derived. The Reference sequence is included in CAM haplotype (black color). Samples from Pregen, which correspond to newborns at Clinics in Bogotá, seem to come from the Atlantic Coast, since they fit quite well into the phylogenetic network: 2 CAR and 1 BEN (Table 7). ATP1 is an atypical haplotype (Table 7).

Shaikho EM, Farrell JJ, Alsultan A, Qutub H, Al-Ali AK, Figueiredo MS, Chui DHK, Farrer LA, Murphy GJ, Mostoslavsky G, et al. 2017. A phased SNP-based classification of sickle cell anemia HBB haplotypes. BMC Genomics. 18(1):608. doi: 10.1186/s12864-017-4013-y.

 PubMedGoogle Scholar

Shriner D, Rotimi C. 2018. Whole-genome-sequence-based haplotypes reveal single origin of the sickle allele during the holocene wet phase. Am J Hum Genet. 102(4):547–556. doi: 10.1016/j.ajhg.2018.02.003.

 PubMed Web of Science ®Google Scholar

Adekile A, Akbulut-Jeradi N, Al Khaldi R, Fernandez MJ, Sukumaran J. 2021. Diagnosis of SCD and HBB haplotyping in the era of personalized medicine: role of next generation sequencing. J Pers Med. 11(6):454. doi: 10.3390/jpm11060454.

 PubMed Web of Science ®Google Scholar

Cruz PRS, Ananina G, Gil-da-Silva-Lopes VL, Simioni M, Menaa F, Bezerra MAC, Domingos IF, Araújo AS, Pellegrino R, Hakonarson H, et al. 2019. Genetic comparison of sickle cell anaemia cohorts from Brazil and the United States reveals high levels of divergence. Sci Rep. 9(1):10896. doi: 10.1038/s41598-019-47313-2.

 PubMedGoogle Scholar

Muniz A, Corral L, Alaez C, Svarch E, Espinosa E, Carbonell N, di Leo R, Felicetti L, Nagel RL, Martinez G. 1995. Sickle cell anemia and beta-gene cluster haplotypes in Cuba. Am J Hematol. 49(2):163–164. doi: 10.1002/ajh.2830490212.

 PubMed Web of Science ®Google Scholar

Rusanova I, Cossio G, Moreno B, Javier Perea F, De Borace RG, Perea M, Escames G, Acuña-Castroviejo D. 2011. β-globin gene cluster haplotypes in sickle cell patients from Panamá. Am J Hum Biol. 23(3):377–380. doi: 10.1002/ajhb.21148.

 PubMed Web of Science ®Google Scholar

Cuéllar-Ambrosi F, Mondragón MC, Figueroa M, Préhu C, Galactéros F, Ruiz-Linares A. 2000. Sickle cell anaemia and beta-globin gene cluster haplotypes in Colombia. Haemoglobin. 24(3):221–225. doi: 10.3109/03630260008997529.

 PubMed Web of Science ®Google Scholar

Fong C, Lizarralde-Iragorri MA, Rojas-Gallardo D, Barreto G. 2013. Frequency and origin of haplotypes associated with the beta-globin gene cluster in individuals with trait and sickle cell anemia in the Atlantic and Pacific coastal regions of Colombia. Genet Mol Biol. 36(4):494–497. doi: 10.1590/S1415-47572013000400005.

 PubMed Web of Science ®Google Scholar

Moreno N, Martínez JA, Blanco Z, Osorio L, Hackshaw P. 2002. Beta-globin gene cluster haplotypes in Venezuelan sickle cell patients from the state of Aragua. Genet Mol Biol. 25(1):21–34. doi: 10.1590/S1415-47572002000100005.

 Web of Science ®Google Scholar

Figueiredo MS, Silva MCBO, Guerreiro JF, Souza GP, Pires ACR, Zago MA. 1994. The heterogeneity of the βS cluster haplotypes in Brazil. Gene Geogr. 8:7–12.

 PubMedGoogle Scholar