Statistical analysis

Quality control Additional sample QC was per- formed using the APT software release 1.12.0 avail- able from Affymetrix®, Inc Santa Clara, CA. Twenty- nine samples were dropped due to low contrast QC. All individuals with inconsistent genders were dropped if the inconsistency could not be resolved; this removed 20 samples. RELPAIR software (Epstein et al. 2000) was used to test for misspecification of pedigree relationships and to obtain a list of problem- atic individuals to be followed up and resolved; all misspecifications were resolved. Seven samples were dropped due to sample genotyping efficiency (<95 %).

Case control association The case control analysis of SA was performed using the modified quasi- likelihood score (MQLS) method, a quasi- likelihood score test that accounts for correlations among individuals to maintain correct type I error rates and tests for allelic association (Thornton and McPeek 2007). MQLS uses a kinship variance/ covariance matrix of inbreeding coefficients and kinship coefficients to account for inbreeding and relatedness between individuals using a specified pedigree structure. Population prevalence for SA of 30 % was specified, consistent with the frequency of SA in the current study. The method is compu- tationally tractable for GWAS. Only analyses of autosomal SNPs were performed.

dropped due to sample genotyping efficiency (<95 %). PLINK (Purcell et al. 2007) statistical software was used both for marker QC and to format data for analysis. Markers included in analyses had a minor allele frequency (MAF) >0.05 and a geno- typing efficiency >95 %; this resulted in the re- moval of 221,982 markers for MAF and 30,303 markers for genotyping efficiency. Markers that did not map to a chromosome, mitochondrial SNPs, and X chromosome SNPs were also exclud- ed (23,997). A goodness of fit test was used to – examine deviations from Hardy Weinberg equilib- rium (HWE) in the most unrelated individuals (166 individuals determined by pairwise kinship coeffi- cients obtained from the KinInbcoef program (Thornton and McPeek 2007)). Markers with strong deviations from HWE (p<1.0×10−7) were removed from the analysis; this removed seven markers. Genotypes on 551 individuals generated by the CAMP dementia study were also available

lege Station, TX, 2008) was used to create summary statistics for demographic data. Generalized estimat- ing equations with an independence correlation matrix and robust standard errors were used to compare SA cases to controls for demographic data using nuclear families as the correlated grouping variable. p values are reported for demographic data analyses.

Results

dominant model at 166.19 Mb, with a 1-LOD-down support interval extending from 164.38 to 169.62 Mb. The peak MHLOD of 3.30 on chromosome 16 was obtained at 23.97 Mb under a recessive model (1-LOD-down support interval, 18.97 to 26.57 Mb). Three peaks were detected under the nonparametric model on chromosomes 10 (peak MLOD* 4.30 at 4.26 Mb, 1-LOD-down support interval 3.28 to 5.59 Mb), 17 (peak MLOD* 3.50 at 10.09 Mb, 1-LOD-down support interval 9.82 to 11.49 Mb), and 20 (peak MLOD* 3.3 at 0.93 Mb, 1-LOD-down support interval 0.58 to 4.07 Mb).

A description of the criteria used to define SA and normally aged control individuals is provided in Ta- ble 1, and a description of the study sample is provid- ed in Table 2. SA cases were slightly younger and had a higher proportion of males than the controls. A larger proportion of SA cases were from Ohio than Indiana, although a majority of participants were from Indiana. SA cases had slightly lower but not statisti- cally different mean body mass index than the control. By design, measures used to define SA (tests of cog- nitive impairment, depression, and physical impair- ment tests) were lower in SA cases than the control.

Association analysis

Multipoint linkage analysis

To assess association under linkage peaks, markers were examined for regionally significant association within the 1-LOD-down support intervals for the five multipoint linkage peaks. Only the association at inter- genic SNP rs205990 (chromosome 6, 164.44 Mb (GRCh37/hg19 build) between quaking homolog KH domain RNA binding (QKI) and phosphodiesterase 10A (PDE10A), p0 2.36×10−5) survived a Bonferroni correction for the number of SNPs located in each 1- LOD-down confidence interval (p<2.8×10−5 on

The results of multipoint genome-wide linkage analy- sis for all chromosomes using parametric affected- only dominant, parametric affected-only recessive, and nonparametric linkage models are summarized in Fig. 1. Five regions of the genome generated multi- point LOD scores (MHLOD or MLOD*) exceeding three under at least one of the models tested. The peak MHLOD of 3.24 on chromosome 6 occurred under a

Table 2 Demographic and clinical characteristics of study

Variable Total Successfully aged (N074) Controls p value (N0263) (N0189) Gender (% male) 42 65 33 <1.0×10−3 Age (mean) 83.20 81.82 83.74 <1.0×10−3 Center (%) Ohio 45 66 37 <1.0×10−3 Indiana 55 34 63 County (%) Adams 9 1 12 <1.0×10−3 Elkhart/LaGrange 46 33 51 Holmes 45 66 37 BMI (mean) 27.74 26.70 28.24 0.024 3MS (median [range]) 92 [58–103] 94 [87–103] 92 [58–101] <1.0×10−3 GDS (median [range]) 2 [0–14] 1 [0–4] 2 [0–14] <1.0×10−3 ADL (median [range]) 0 [0–9] 0 [0–1] 1 [0–9] <1.0×10−3 IADL (Median [range]) 0 [0–12] 0 [0–1] 1 [0–12] <1.0×10−3 Nagi (median [range]) 1 [0–5] 0 [0–1] 2 [0–5] <1.0×10−3 Rosow–Breslau (median [range]) 3 [3–6] 3 [3–4] 4 [3–6] <1.0×10−3 EPESE (median [range]) 8 [0–12] 10 [9–12] 7 [0–12] <1.0×10−3

  

MLOD* for the nonparametric multipoint model (green or lightest gray line) are presented in this figure

Fig. 1 Multipoint linkage results for all chromosomes. MHLOD for the dominant multipoint model (red or moderate gray line), recessive multipoint model (blue or darkest gray line), and