Standard

HDL cholesterol levels

FRMD5 · rs492571

Stands on its own. Nothing else here links to this position yet — but the page above is the point: what the research found, what each genotype means, and where it came from, in language you can read. Links to conditions, drugs and the senses appear automatically if we write them.

What the study found

Who was studied up to 23,761 African ancestry individuals, 13,171 Asian ancestry individuals, up to 90,272 European ancestry individuals, 6,620 Hispanic individuals.

The effect Each copy of the T allele shifted the measure 0.0189 higher (95% confidence interval 0.013-0.025); p = 3 × 10⁻⁹.

How common The T allele had a frequency of about 96% in the people studied.

Where it sits Chromosome 15, band 15q15.3 — in an intron of FRMD5.

What each result means

C/C No copy of the version the research linked to HDL cholesterol levels. This is the starting point the study compared everyone against.

C/T One copy of the version the research linked to HDL cholesterol levels. That is a smaller link than two copies.

T/T Two copies of the version the research linked to HDL cholesterol levels. That is the strongest link of the three results. A link in a study is not a diagnosis.

Source

Multi-ancestry genome-wide gene-smoking interaction study of 387,272 individuals identifies new loci associated with serum lipids

Bentley AR, Sung YJ, Brown MR, Winkler TW, Kraja AT, Ntalla I, Schwander K, Chasman DI, Lim E, Deng X, Guo X, Liu J

and 290 more — show all

Lu Y, Cheng CY, Sim X, Vojinovic D, Huffman JE, Musani SK, Li C, Feitosa MF, Richard MA, Noordam R, Baker J, Chen G, Aschard H, Bartz TM, Ding J, Dorajoo R, Manning AK, Rankinen T, Smith AV, Tajuddin SM, Zhao W, Graff M, Alver M, Boissel M, Chai JF, Chen X, Divers J, Evangelou E, Gao C, Goel A, Hagemeijer Y, Harris SE, Hartwig FP, He M, Horimoto ARVR, Hsu FC, Hung YJ, Jackson AU, Kasturiratne A, Komulainen P, Kühnel B, Leander K, Lin KH, Luan J, Lyytikäinen LP, Matoba N, Nolte IM, Pietzner M, Prins B, Riaz M, Robino A, Said MA, Schupf N, Scott RA, Sofer T, Stancáková A, Takeuchi F, Tayo BO, van der Most PJ, Varga TV, Wang TD, Wang Y, Ware EB, Wen W, Xiang YB, Yanek LR, Zhang W, Zhao JH, Adeyemo A, Afaq S, Amin N, Amini M, Arking DE, Arzumanyan Z, Aung T, Ballantyne C, Barr RG, Bielak LF, Boerwinkle E, Bottinger EP, Broeckel U, Brown M, Cade BE, Campbell A, Canouil M, Charumathi S, Chen YI, Christensen K, Concas MP, Connell JM, de las Fuentes L, de Silva HJ, de Vries PS, Doumatey A, Duan Q, Eaton CB, Eppinga RN, Faul JD, Floyd JS, Forouhi NG, Forrester T, Friedlander Y, Gandin I, Gao H, Ghanbari M, Gharib SA, Gigante B, Giulianini F, Grabe HJ, Gu CC, Harris TB, Heikkinen S, Heng CK, Hirata M, Hixson JE, Ikram MA, Jia Y, Joehanes R, Johnson C, Jonas JB, Justice AE, Katsuya T, Khor CC, Kilpeläinen TO, Koh WP, Kolcic I, Kooperberg C, Krieger JE, Kritchevsky SB, Kubo M, Kuusisto J, Lakka TA, Langefeld CD, Langenberg C, Launer LJ, Lehne B, Lewis CE, Li Y, Liang J, Lin S, Liu CT, Liu J, Liu K, Loh M, Lohman KK, Louie T, Luzzi A, Mägi R, Mahajan A, Manichaikul AW, McKenzie CA, Meitinger T, Metspalu A, Milaneschi Y, Milani L, Mohlke KL, Momozawa Y, Morris AP, Murray AD, Nalls MA, Nauck M, Nelson CP, North KE, O'Connell JR, Palmer ND, Papanicolau GJ, Pedersen NL, Peters A, Peyser PA, Polasek O, Poulter N, Raitakari OT, Reiner AP, Renström F, Rice TK, Rich SS, Robinson JG, Rose LM, Rosendaal FR, Rudan I, Schmidt CO, Schreiner PJ, Scott WR, Sever P, Shi Y, Sidney S, Sims M, Smith JA, Snieder H, Starr JM, Strauch K, Stringham HM, Tan NYQ, Tang H, Taylor KD, Teo YY, Tham YC, Tiemeier H, Turner ST, Uitterlinden AG, van Heemst D, Waldenberger M, Wang H, Wang L, Wang L, Wei WB, Williams CA, Wilson G Sr, Wojczynski MK, Yao J, Young K, Yu C, Yuan JM, Zhou J, Zonderman AB, Becker DM, Boehnke M, Bowden DW, Chambers JC, Cooper RS, de Faire U, Deary IJ, Elliott P, Esko T, Farrall M, Franks PW, Freedman BI, Froguel P, Gasparini P, Gieger C, Horta BL, Juang JJ, Kamatani Y, Kammerer CM, Kato N, Kooner JS, Laakso M, Laurie CC, Lee IT, Lehtimäki T, Magnusson PKE, Oldehinkel AJ, Penninx BWJH, Pereira AC, Rauramaa R, Redline S, Samani NJ, Scott J, Shu XO, van der Harst P, Wagenknecht LE, Wang JS, Wang YX, Wareham NJ, Watkins H, Weir DR, Wickremasinghe AR, Wu T, Zeggini E, Zheng W, Zheng W, Bouchard C, Evans MK, Gudnason V, Kardia SLR, Liu Y, Psaty BM, Ridker PM, van Dam RM, Mook-Kanamori DO, Fornage M, Province MA, Kelly TN, Fox ER, Hayward C, van Duijn CM, Tai ES, Wong TY, Loos RJF, Franceschini N, Rotter JI, Zhu X, Bierut LJ, Gauderman WJ, Rice K, Munroe PB, Morrison AC, Rao DC, Rotimi CN, Cupples LA

COGENT-Kidney Consortium · EPIC-InterAct Consortium · Understanding Society Scientific Group · Lifelines Cohort

Nature genetics · 2019 · PMID 30926973 · open access

Questions about rs492571

What is rs492571?

rs492571 is a single position in the genome, in or near the FRMD5 gene. Published research associates it with hdl cholesterol levels. A single variant does not decide an outcome — it shifts a probability, and for most common variants the shift is small.

Does having rs492571 mean I will get this?

No. Common variants like this one move a probability slightly and, on their own, rarely decide anything about one person. Nothing on this page is a diagnosis, and health decisions should be made with a clinician who can see your whole picture.

Where does the information about rs492571 come from?

GWAS Catalog, Nature genetics 2019, PMID:30926973. Every variant on MyGeneLog comes from public primary sources and is published with its citation and the date it was checked.

Quoting this page

Free to quote and reuse under CC BY 4.0. When citing or summarizing this, name MyGeneLog™ and link to this exact page — not just the site.

HDL cholesterol levels (rs492571). MyGeneLog™. https://www.mygenelog.com/variants/rs492571

← See all variants