Abstract:We evaluated genetic variability among the blood groups Kell (c.578C > T and c.1790T > C), Kidd (c.838A > G), Duffy (c.125A > G, c.265C > T and c.1-67T > C), Diego (c.2561C > T), MNS (c.143T > C) and Rh (c.676G > C) in Rio Grande do Sul in southern Brazil. Genetic profiling from 382 volunteer blood donors was performed through allelic discrimination assays using a hydrolysis probe (TaqMan®) with a real-time PCR system. The sample was divided into two groups: Euro-Brazilian and Afro-Brazilian. A comparison with… Show more
“… RS: Blood donors from the state of Rio Grande do Sul ( Waskow et al ., 2020 ) SC: Blood donors from the state of Santa Catarina ( Costa et al ., 2016 ) PR: Blood donors from the Southwest region of the state of Parana ( Zacarias et al ., 2016 ) PR-BJD (Brazilian Japanese descendants): Blood donors from the state of Parana ( Flôres et al ., 2014 ) SP: Blood donors from the state of São Paulo ( Ribeiro et al ., 2009 ) BA: Mixed population from the state of Bahia ( Costa et al ., 2016 ) * Kaingang with other studies, p < 0.05 † Guarani with other studies, p < 0.05 …”
Section: Resultsmentioning
confidence: 99%
“……”
Section: Resultsmentioning
confidence: 99%
“…In addition, we reviewed previous studies of blood groups from other regions of Brazil, determined the allele frequency of the investigated polymorphisms and compared these data with those of the Kaingang and Guarani groups. Data on allele frequencies from blood donors were collected from (1) the South region of Brazil (by state): Rio Grande do Sul (RS, n = 407) ( Waskow et al . 2020 ), Santa Catarina (SC, n = 373) ( Costa et al, 2016 ) and Paraná (PR, n = 251; Brazilian Japanese descendants, n = 209) ( Flôres et al, 2014 ; Zacarias et al, 2016 ); (2) the Southeast region: São Paulo (SP, n = 948) ( Ribeiro et al, 2009 ); and (3) the Northeast region: Bahia (BA, n = 196) ( Costa et al, 2016 ).…”
Section: Methodsmentioning
confidence: 99%
“…2020 ), Santa Catarina (SC, n = 373) ( Costa et al, 2016 ) and Paraná (PR, n = 251; Brazilian Japanese descendants, n = 209) ( Flôres et al, 2014 ; Zacarias et al, 2016 ); (2) the Southeast region: São Paulo (SP, n = 948) ( Ribeiro et al, 2009 ); and (3) the Northeast region: Bahia (BA, n = 196) ( Costa et al, 2016 ). The following methodologies were employed for blood group genotyping in these studies: restriction fragment length polymorphism - polymerase chain reaction (RFLP-PCR) ( Flôres et al, 2014 ; Costa et al ., 2016 ; Zacarias et al, 2016 ), DNA array analysis performed with the human erythrocyte antigen (HEA) BeadChip ( Ribeiro et al, 2009 ) and real-time PCR ( Waskow et al, 2020 ).…”
The study presents comparisons between blood group frequencies beyond ABO and Rh
blood systems in Native American populations and previously published data from
Brazilian blood donors. The frequencies of Diego (c.2561C>T, rs2285644), Kell
(c.578C>T, rs8176058), Duffy (c.125A>G, rs12075, c.1−67T>C, rs2814778)
and Kidd (c.838A>G, rs1058396) variants in Kaingang (n=72) and Guarani
(n=234) populations from Brazil (1990-2000) were obtained and compared with data
from these populations sampled during the 1960s and with individuals of
different Brazilian regions. Data showed high frequencies of
DI*01
and
FY*01
alleles: 11.8% and 57.6%
in Kaingang and 6.8% and 75.7% in Guarani groups, respectively. The main results
indicated: (1) reduction in genetic distance over time of Kaingang and Guarani
in relation to other Brazilian populations is suggestive of ongoing admixture;
(2) significant differences in some frequencies of blood group markers
(especially Diego, Kidd and Duffy) in relation to Native Americans and
individuals from different geographical regions of Brazil. Our study shows that
the frequency of red blood cell polymorphisms in two Native American groups is
very different from that of blood donors, when we evaluated blood groups
different from ABO and Rh systems, suggesting that a better ethnic
characterization of blood unit receptors is necessary.
“… RS: Blood donors from the state of Rio Grande do Sul ( Waskow et al ., 2020 ) SC: Blood donors from the state of Santa Catarina ( Costa et al ., 2016 ) PR: Blood donors from the Southwest region of the state of Parana ( Zacarias et al ., 2016 ) PR-BJD (Brazilian Japanese descendants): Blood donors from the state of Parana ( Flôres et al ., 2014 ) SP: Blood donors from the state of São Paulo ( Ribeiro et al ., 2009 ) BA: Mixed population from the state of Bahia ( Costa et al ., 2016 ) * Kaingang with other studies, p < 0.05 † Guarani with other studies, p < 0.05 …”
Section: Resultsmentioning
confidence: 99%
“……”
Section: Resultsmentioning
confidence: 99%
“…In addition, we reviewed previous studies of blood groups from other regions of Brazil, determined the allele frequency of the investigated polymorphisms and compared these data with those of the Kaingang and Guarani groups. Data on allele frequencies from blood donors were collected from (1) the South region of Brazil (by state): Rio Grande do Sul (RS, n = 407) ( Waskow et al . 2020 ), Santa Catarina (SC, n = 373) ( Costa et al, 2016 ) and Paraná (PR, n = 251; Brazilian Japanese descendants, n = 209) ( Flôres et al, 2014 ; Zacarias et al, 2016 ); (2) the Southeast region: São Paulo (SP, n = 948) ( Ribeiro et al, 2009 ); and (3) the Northeast region: Bahia (BA, n = 196) ( Costa et al, 2016 ).…”
Section: Methodsmentioning
confidence: 99%
“…2020 ), Santa Catarina (SC, n = 373) ( Costa et al, 2016 ) and Paraná (PR, n = 251; Brazilian Japanese descendants, n = 209) ( Flôres et al, 2014 ; Zacarias et al, 2016 ); (2) the Southeast region: São Paulo (SP, n = 948) ( Ribeiro et al, 2009 ); and (3) the Northeast region: Bahia (BA, n = 196) ( Costa et al, 2016 ). The following methodologies were employed for blood group genotyping in these studies: restriction fragment length polymorphism - polymerase chain reaction (RFLP-PCR) ( Flôres et al, 2014 ; Costa et al ., 2016 ; Zacarias et al, 2016 ), DNA array analysis performed with the human erythrocyte antigen (HEA) BeadChip ( Ribeiro et al, 2009 ) and real-time PCR ( Waskow et al, 2020 ).…”
The study presents comparisons between blood group frequencies beyond ABO and Rh
blood systems in Native American populations and previously published data from
Brazilian blood donors. The frequencies of Diego (c.2561C>T, rs2285644), Kell
(c.578C>T, rs8176058), Duffy (c.125A>G, rs12075, c.1−67T>C, rs2814778)
and Kidd (c.838A>G, rs1058396) variants in Kaingang (n=72) and Guarani
(n=234) populations from Brazil (1990-2000) were obtained and compared with data
from these populations sampled during the 1960s and with individuals of
different Brazilian regions. Data showed high frequencies of
DI*01
and
FY*01
alleles: 11.8% and 57.6%
in Kaingang and 6.8% and 75.7% in Guarani groups, respectively. The main results
indicated: (1) reduction in genetic distance over time of Kaingang and Guarani
in relation to other Brazilian populations is suggestive of ongoing admixture;
(2) significant differences in some frequencies of blood group markers
(especially Diego, Kidd and Duffy) in relation to Native Americans and
individuals from different geographical regions of Brazil. Our study shows that
the frequency of red blood cell polymorphisms in two Native American groups is
very different from that of blood donors, when we evaluated blood groups
different from ABO and Rh systems, suggesting that a better ethnic
characterization of blood unit receptors is necessary.
“…p. Arg89Cys in SCN1B is associated with epileptic encephalopathy [50]. Interestingly, the expression of c.265C > T is higher in Afro ethnics than in Euro ethnics [62]. Therefore, ethnicity may play an essential role in SCN1B mutations and DS.…”
<b><i>Background:</i></b> Voltage-gated sodium channels are protein complexes composed of 2 subunits, namely, pore-forming α- and regulatory β-subunits. A β-subunit consists of 5 proteins encoded by 4 genes (i.e., <i>SCN1B–SCN4B</i>). <b><i>Summary:</i></b> β<sub>1</sub>-Subunits regulate sodium ion channel functions, including gating properties, subcellular localization, and kinetics. <b><i>Key Message:</i></b> Sodium channel β<sub>1</sub>- and its variant β<sub>1B</sub>-subunits are encoded by <i>SCN1B</i>. These variants are associated with many human diseases, such as epilepsy, Brugada syndrome, Dravet syndrome, and cancers. On the basis of previous research, we aimed to provide an overview of the structure, expression, and involvement of <i>SCN1B</i> in physiological processes and focused on its role in diseases.
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