title: Considerations for subgroups and phenocopies in complex disease genetics.
abstract: The number of identified genetic variants associated to complex disease cannot fully explain heritability. This may be partially due to more complicated patterns of predisposition than previously suspected. Diseases such as multiple sclerosis (MS) may consist of multiple disease causing mechanisms, each comprised of several elements. We describe how the effect of subgroups can be calculated using the standard association measurement odds ratio, which is then manipulated to provide a formula for the true underlying association present within the subgroup. This is sensitive to the initial minor allele frequencies present in both cases and the subgroup of patients. The methodology is then extended to the χ(2) statistic, for two related scenarios. First, to determine the true χ(2) when phenocopies or disease subtypes reduce association and are reclassified as controls when calculating statistics. Here, the χ(2) is given by (1 + σ * (a + b)/(c + d))/(1 - σ), or (1 + σ)/(1 - σ) for equal numbers of cases and controls. Second, when subgroups corresponding to heterogeneity mask the true effect size, but no reclassification is made. Here, the proportion increase in total sample size required to attain the same χ(2) statistic as the subgroup is given as γ = (1 - σ/2)/((1 - σ)(1 - σc/(a + c))(1 - σd/(b + d))), and a python script to calculate and plot this value is provided at kirc.se. Practical examples show how in a study of modest size (1000 cases and 1000 controls), a non-significant SNP may exceed genome-wide significance when corresponding to a subgroup of 20% of cases, and may occur in heterozygous form in all cases. This methodology may explain the modest association found in diseases such as MS wherein heterogeneity confounds straightforward measurement of association.
authors: Department of Clinical Neuroscience, Karolinska Institutet at Karolinska University Hospital Solna, Stockholm, Sweden.
authors: Ryan
authors: R
authors: Ramanujam
authors: S
authors: S
authors: Ramanujam
authors: Jan
authors: J
authors: Hillert
mesh_terms: D000483:Alleles; D016009:Chi-Square Distribution; D004194:Disease / Q000235:genetics*; D005787:Gene Frequency; D018740:Genetic Heterogeneity; D020022:Genetic Predisposition to Disease; D006801:Humans; D008957:Models, Genetic; D016017:Odds Ratio; D010641:Phenotype; D018401:Sample Size
references: Expert Rev Neurother. 2009 Mar;9(3):351-8
references: 19271944
references: PLoS One. 2007 Jul 25;2(7):e664
references: 17653284
references: Am J Public Health. 2005;95 Suppl 1:S144-50
references: 16030331
references: Arch Neurol. 2007 Dec;64(12):1729-33
references: 18071035
references: Ann Rheum Dis. 2004 Sep;63(9):1085-9
references: 15308517
references: Nature. 2003 May 15;423(6937):356-61
references: 12748655
references: Ann Rheum Dis. 2011 Feb;70(2):259-65
references: 21156761
references: Twin Res Hum Genet. 2011 Apr;14(2):129-36
references: 21425894
references: Am J Respir Crit Care Med. 1997 Oct;156(4 Pt 2):S103-9
references: 9351588
references: Nature. 2011 Aug 10;476(7359):214-9
references: 21833088
references: Curr Opin Rheumatol. 2012 Sep;24(5):482-8
references: 22732687
references: Genet Epidemiol. 2011 Jul;35(5):310-7
references: 21374718
references: Semin Surg Oncol. 1985;1(3):139-52
references: 2414838
references: Eur J Hum Genet. 2010 Aug;18(8):960-4
references: 20354561
references: Nature. 2009 Oct 8;461(7265):747-53
references: 19812666
references: Ann Neurol. 2000 Aug;48(2):211-9
references: 10939572
references: Sci Rep. 2012;2:770
references: 23105968