Population differentiation in allele frequencies of obesity-associated SNPs

Abstract

BackgroundObesity is emerging as a global health problem, with more than one-third of the world’s adult population being overweight or obese. In this study, we investigated worldwide population differentiation in allele frequencies of obesity-associated SNPs (single nucleotide polymorphisms).ResultsWe collected a total of 225 obesity-associated SNPs from a public database. Their population-level allele frequencies were derived based on the genotype data from 1000 Genomes Project (phase 3). We used hypergeometric model to assess whether the effect allele at a given SNP is significantly enriched or depleted in each of the 26 populations surveyed in the 1000 Genomes Project with respect to the overall pooled population. Our results indicate that 195 out of 225 SNPs (86.7%) possess effect alleles significantly enriched or depleted in at least one of the 26 populations. Populations within the same continental group exhibit similar allele enrichment/depletion patterns whereas inter-continental populations show distinct patterns. Among the 225 SNPs, 15 SNPs cluster in the first intron region of the FTO gene, which is a major gene associated with body-mass index (BMI) and fat mass. African populations exhibit much smaller blocks of LD (linkage disequilibrium) among these15 SNPs while European and Asian populations have larger blocks. To estimate the cumulative effect of all variants associated with obesity, we developed the personal composite genetic risk score for obesity. Our results indicate that the East Asian populations have the lowest averages of the composite risk scores, whereas three European populations have the highest averages. In addition, the population-level average of composite genetic risk scores is significantly correlated (R2 = 0.35, P = 0.0060) with obesity prevalence.ConclusionsWe have detected substantial population differentiation in allele frequencies of obesity-associated SNPs. The results will help elucidate the genetic basis which may contribute to population disparities in obesity prevalence.Electronic supplementary materialThe online version of this article (10.1186/s12864-017-4262-9) contains supplementary material, which is available to authorized users.

Latitude variation of the uncoupling proteins gene frequencies for obesity in human populations

“…Ïàòòåðí ðàñïðåäåëåíèÿ «áåðåaeëèâûõ» àëëåëåé ðèñêà ðàçâèòèÿ îaeèðåíèÿ, à èìåííî ãåíîâ UCP1-3, ñïåöèôè÷åí äëÿ ðàçëè÷íûõ ïîïóëÿöèé, îáèòàþùèõ â ðàçëè÷íûõ êëèìàòè÷åñêèõ çîíàõ [Salopuro et al 2009;Brondani et al, 2014;Chathoth et al, 2018]. Ìàî è Ìàð÷èíè [Marchini et al, 2004;Mao et al, 2017] ÷òî îò ÷àñòè ìåaeïîïóëÿöèîííûå ðàçëè÷èÿ îáóñëîâëåíû øèðîòíîé èçìåí÷èâîñòüþ «òåðìîãåííûõ» è «áåðåaeëèâûõ» àëëåëåé ðàçîáùàþùèõ áåëêîâ. Ëþäè, àäàïòèðîâàâøèåñÿ ê ïðîaeèâàíèþ â âûñîêèõ øèðîòàõ, èìåþò ìåíüøèé ïîïóëÿöèîííûé ðèñê ðàçâèòèÿ îaeèðåíèÿ è êîìîðáèäíûõ åìó çàáîëåâàíèé, â ñâÿçè ñ âûñîêîé ÷àñòîòîé âñòðå÷àåìîñòè ó íèõ «òåðìîãåííûõ» àëëåëåé ðàçîáùàþùèõ áåëêîâ.…”

“…Ëþäè, àäàïòèðîâàâøèåñÿ ê ïðîaeèâàíèþ â âûñîêèõ øèðîòàõ, èìåþò ìåíüøèé ïîïóëÿöèîííûé ðèñê ðàçâèòèÿ îaeèðåíèÿ è êîìîðáèäíûõ åìó çàáîëåâàíèé, â ñâÿçè ñ âûñîêîé ÷àñòîòîé âñòðå÷àåìîñòè ó íèõ «òåðìîãåííûõ» àëëåëåé ðàçîáùàþùèõ áåëêîâ.  òî aeå âðåìÿ ðàñïðîñòðàíåííîñòü îaeèðåíèÿ â ñòðàíàõ Âîñòî÷íîé Àçèè íèaeå ïî ñðàâíåíèþ ñ åâðîïåéñêèìè ñòðàíàìè, ÷òî ìîaeåò ãîâîðèòü î áîëüøåì âëèÿíèè ñîöèîêóëüòóðíûõ ôàêòîðîâ [Mao et al, 2017]. Àäàïòàöèÿ ê ëîêàëüíûì óñëîâèÿì ñðåäû âñëåäñòâèå âîçäåéñòâèÿ êîìïëåêñà àáèîòè÷åñêèõ ôàêòîðîâ, à òàêaeå äèåòû è èçìåíåíèå îáðàçà aeèçíè ìîãëè ñòàòü ïðè÷èíîé èçìåíåíèÿ ÷àñòîò âñòðå÷àåìîñòè àëëåëåé ãåíîâ ðàçîáùàþùèõ áåëêîâ, ÷òî, â ñâîþ î÷åðåäü, â íåêîòîðûõ ñîâðåìåííûõ ïîïóëÿöèÿõ ìîaeåò ïðèâîäèòü ê óâå-ëè÷åíèþ ðèñêà îaeèðåíèÿ íà ôîíå ãèïîäèíàìèè è ïîëèôàãèè.…”

Comparison of Risk Allele Frequencies of Single Nucleotide Polymorphisms Associated With Age-Related Macular Degeneration in Different Ethnic Groups

“…To compare the composite genetic risk of AMD, we adopted the following equation described by Mao et al [19]. : (see Equation 1 in the Supplementary Files)…”

Obesity predisposition associated with FTO gene polymorphism among different ethnic groups of Russia and Mongolia

“…Ïîëíîãåíîìíûå èññëåäîâàíèÿ, ïðîâåäåííûå çà ïîñëåäíåå âðåìÿ, ïîçâîëèëè îáíàðóaeèòü ñîòíè ëîêóñîâ ãåíîìà ÷åëîâåêà, àññîöèèðîâàííûõ ñ èíäåêñîì ìàññû òåëà (ÈÌÒ), îaeèðåíèåì è ìåòàáîëè÷åñêèì ñèíäðîìîì. Ôàêòè÷åñêè íàñûùåííîñòü ãåíîôîíäà ïîïóëÿöèè àëëåëÿìè ðèñêà îaeèðåíèÿ ñîâïàäàåò ñ äîëåé íàñåëåíèÿ â äàííîé ïîïóëÿöèè, ñòðàäàþùåãî îaeèðåíèåì è èç-áûòî÷íûì âåñîì [Mao et al, 2017]. Îäíîíóêëåîòèäíûå çàìåíû, àññîöèèðîâàííûå ñ ïîâûøåííîé ñêëîííîñòüþ ê íàáîðó aeèðà è, êàê ñëåäñòâèå, ñ ðèñêîì îaeèðåíèÿ è êîìîðáèäíûõ åìó çàáîëåâàíèé, ëîêàëèçîâàíû â ïåðâîì èíòðîíå ãåíà, àññîöèèðîâàííîãî ñ aeèðîâîé ìàññîé è îaeèðåíèåì (FTOfat mass and obesity associated).…”

“…Èç íèõ 14 äåìîíñòðèðóþò êðàéíå âûñîêèé óðîâåíü ñöåïëåíèÿ â ïîïóëÿöèÿõ Åâðîïû, è óìåðåííî âûñîêèé äëÿ íàñåëåíèÿ Àìåðèêè, Âîñòî÷íîé è Þaeíîé Àçèè. Àëëåëè ðèñêà FTO, ëîêàëèçîâàííûå â ïåðâîì èíòðîíå ãåíà, íåðàâíîìåðíî ðàñïðåäåëåíû â ïîïóëÿöèÿõ ñîâðåìåííîãî ÷åëîâåêà, òàê íàèáîëåå íàñûùåííûìè äàííûìè àëëåëÿìè îêàçàëèñü ïîïóëÿöèè Åâðîïû è Ñåâåðíîé Àìåðèêè, òîãäà êàê ïîïóëÿöèè Âîñòî÷íîé Àçèè îáåäíåíû äàííûìè àëëåëÿìè [Mao et al, 2017]. Çàìåíû â ïåðâîì èíòðîíå FTO äåìîíñòðèðóþò ñèëüíîå âëèÿíèå íà çíà÷åíèå ÈÌÒ, ÷òî ïîäòâåðaeäàåò êëþ÷åâóþ ðîëü äàííîãî ãåíà â ðåãóëÿöèè âåñà [Speliotes et al, 2010;Locke et al, 2015].…”