{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,24]],"date-time":"2025-04-24T04:24:09Z","timestamp":1745468649244,"version":"3.40.4"},"reference-count":48,"publisher":"S. Karger AG","issue":"4","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Lifestyle Genomics"],"published-print":{"date-parts":[[2022]]},"abstract":"<b><i>Introduction:<\/i><\/b> \u201cQuantile-dependent expressivity\u201d occurs when the effect size of a genetic variant depends upon whether the phenotype (e.g., mean platelet volume, MPV) is high or low relative to its distribution. <b><i>Methods:<\/i><\/b> Offspring-parent regression slopes (\u03b2<sub>OP<\/sub>) were estimated by quantile regression, from which quantile-specific heritabilities (<i>h<\/i><sup>2<\/sup>) were calculated (<i>h<\/i><sup>2<\/sup> = 2\u03b2<sub>OP<\/sub>\/[1 + <i>r<\/i><sub>spouse<\/sub>]) for blood cell phenotypes in 3,929 parent-offspring pairs from the Framingham Heart Study. <b><i>Results:<\/i><\/b> Quantile-specific <i>h<\/i><sup>2<\/sup> (\u00b1SE) increased with increasing percentiles of the offspring\u2019s age- and sex-adjusted MPV distribution (<i>p<\/i><sub>linear<\/sub> = 0.0001): 0.48 \u00b1 0.09 at the 10th, 0.53 \u00b1 0.04 at the 25th, 0.70 \u00b1 0.06 at the 50th, 0.74 \u00b1 0.06 at the 75th, and 0.90 \u00b1 0.12 at the 90th percentile. Quantile-specific <i>h<\/i><sup>2<\/sup> also increased with increasing percentiles of the offspring\u2019s white blood cell (WBC, <i>p<\/i><sub>linear<\/sub> = 0.002), monocyte (<i>p<\/i><sub>linear<\/sub> = 0.01), and eosinophil distributions (<i>p<\/i><sub>linear<\/sub> = 0.0005). In contrast, heritibilities of red blood cell (RBC) count, hematocrit (HCT), and hemoglobin (HGB) showed little evidence of quantile dependence. Quantile-dependent expressivity is consistent with gene-environment interactions reported by others, including (1) greater increases in WBC and PLT concentrations in subjects who are glutathione-S-transferase Mu1 (<i>GSTM1<\/i>) null homozygotes than <i>GSTM1<\/i> sufficient when exposed to endotoxin; (2) significantly higher WBC count in AA homozygotes than carriers of the G-allele of the glutathione S-transferase P1 (<i>GSTP1<\/i>) rs1695 polymorphism at low but not high benzene exposure in shoe factory workers; (3) higher WBC counts in TT homozygotes than C-allele carriers of the interleukin-1\u03b2 (<i>IL1B<\/i>) c.315C&#x3e;T polymorphism after undergoing surgery for infective endocarditis but not before surgery. <b><i>Discussion\/Conclusion:<\/i><\/b> Quantile-dependent expressivity may explain several purported gene-environment interactions involving blood cell phenotypes. <\/jats:p>","DOI":"10.1159\/000527048","type":"journal-article","created":{"date-parts":[[2022,9,22]],"date-time":"2022-09-22T21:00:43Z","timestamp":1663880443000},"page":"111-123","source":"Crossref","is-referenced-by-count":1,"title":["Quantile-Specific Heritability of Mean Platelet Volume, Leukocyte Count, and Other Blood Cell Phenotypes"],"prefix":"10.1159","volume":"15","author":[{"given":"Paul T.","family":"Williams","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"127","published-online":{"date-parts":[[2022,9,22]]},"reference":[{"key":"ref1"},{"key":"ref2"},{"key":"ref3"},{"key":"ref4"},{"key":"ref5"},{"key":"ref6"},{"key":"ref7"},{"key":"ref8"},{"key":"ref9"},{"key":"ref10"},{"key":"ref11"},{"key":"ref12"},{"key":"ref13"},{"key":"ref14"},{"key":"ref15"},{"key":"ref16"},{"key":"ref17"},{"key":"ref18"},{"key":"ref19"},{"key":"ref20"},{"key":"ref21"},{"key":"ref22"},{"key":"ref23"},{"key":"ref24"},{"key":"ref25"},{"key":"ref26"},{"key":"ref27"},{"key":"ref28"},{"key":"ref29"},{"key":"ref30"},{"key":"ref31"},{"key":"ref32"},{"key":"ref33"},{"key":"ref34"},{"key":"ref35"},{"key":"ref36"},{"key":"ref37"},{"key":"ref38"},{"key":"ref39"},{"key":"ref40"},{"key":"ref41"},{"key":"ref42"},{"key":"ref43"},{"key":"ref44"},{"key":"ref45"},{"key":"ref46"},{"key":"ref47"},{"key":"ref48"}],"container-title":["Lifestyle Genomics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.karger.com\/Article\/Pdf\/527048","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.karger.com\/Article\/Pdf\/527048","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,23]],"date-time":"2025-04-23T15:22:38Z","timestamp":1745421758000},"score":1,"resource":{"primary":{"URL":"https:\/\/karger.com\/article\/doi\/10.1159\/000527048"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":48,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2022,11,22]]}},"URL":"https:\/\/doi.org\/10.1159\/000527048","archive":["Portico"],"relation":{},"ISSN":["2504-3161","2504-3188"],"issn-type":[{"type":"print","value":"2504-3161"},{"type":"electronic","value":"2504-3188"}],"subject":[],"published":{"date-parts":[[2022]]}}}