Promoter analysis of LASS1 haplotypes

The two polymorphisms in the coding region (rs429358 and rs7412) account for the occurrence of three alleles, e2, e3, and e4, which result in the three major isoforms, E2, E3, and E4 of APOE, respectively. The E2, E3, and E4 isoforms differ on amino acid sequence at site A (residue number 112) and site B (residue number 158) in exon 4. For HRAS1 and LASS1 SNP, their loca- tions are relative to the first nucleotide of the translation start codon, whereas the transcription start site was used for the APOE SNP.

A 1755-bp DNA fragment containing the putative promoter region and part of the coding region of LASS1 was PCR-ampli- fied from appropriate genomic DNA samples using EcoRV and BglII-tagged primers and cloned into the Pgl4.10 vector (Pro- mega, Sunnyvale, CA, USA). The cloned sequence is in frame with the firefly luciferase coding sequence in the vector. Then, an additional 1040-bp fragment tagged with XhoI and EcoRV was added upstream of the original clone. The translational start codon of LASS1 was changed to TAG by site-directed mutagen- esis. The correctness of the final constructs was verified by sequencing. The only sequence differences between the con- structs were at the polymorphic sites of interest specified below. Transfection of HeLa cells was performed using the PolyFect

Population stratification using Structure

Identification of ethnic origins of individuals using Alu insertion polymorphisms was performed as described (Bamshad et al., 2003; Watkins et al., 2003; Ray et al., 2005). DNA samples were genotyped at 100 separate Alu loci located throughout

transfection reagent (Qiagen, Valencia, CA, USA) per the tocol provided. Co-transfection was carried out with

of one of the experimental constructs (0.4 lg) with a control vector, Pgl4.73 (10 ng), which carries a Renilla luciferase cod- ing sequence under the SV40 promoter. The experimental con- structs were either Pgl4.10 without LASS1 promoter sequences or Pgl4.10 with one of three different LASS1 sequences. These had the following bases at positions )718, +216, and +234, respectively: AGC, CCT, or CGT. Following 24-h incubation, luciferase activities were measured using the Dual-Glo Luciferase Assay (Promega) per the protocol provided, using a Modulus Microplate Luminometer (Turner BioSystems, Sunnyvale, CA, USA). The firefly luminescence readings were normalized to the Renilla luminescence readings. There were at least six replicates of each assay per experiment.

APOE allele frequencies and genotype frequencies were com- pared between centenarians⁄nonagenarians and young con- trols with a 2 · 3 contingency table (for alleles) or with a 2 · 6 contingency table (for genotypes). The contingency tables were evaluated by Fisher’s exact probability test (Sanchez et al., 2006), using SAS v9.13 software (SAS Institute Inc., Cary, NC, USA). A P-value < 0.05 was considered statistically significant. All statistical tests of significance reported in this study are two-sided.

Structure v2.2 (Pritchard et al., 2000) was used to infer popu- lation structure for the 650 Georgia subjects and the 869 Louisi- ana subjects, respectively. Seven hundred and fifteen subjects of known geographic ancestry (European, African, Asian, or Indian) were used as reference. For each individual, Structure 2.2 estimates the proportion of ancestry from each of four pop- ulations. We used a burn-in of 15 000 iterations and a run of 20 000 replications. Three replicate runs were performed on each dataset. The largest proportion values in each run were used to calculate the average ancestry proportion for each indi- vidual. Individuals were either assigned to a specific geographic origin if the average was larger than a predetermined assign- ment probability (0.9 in this study) or considered admixed if the average was less. All haplotype analyses were performed on samples stratified for ethnic affiliation, as described here.

Deficit index

Following previously published reports (Kulminski et al., 2008; Searle et al., 2008), our deficit index was derived as the un-weighted count of the number of deficits divided by the total number of possible deficits for an individual. The self-reported medical history questionnaire was administered to all study par- ticipants, and its components were used to construct the deficit index. This was supplemented with items from an activities of daily living (ADL) questionnaire. Responses were grouped to create broader categories where similar ailments were defined more than once. After applying the above criteria, 42 deficits were included in the compilation of the index.