Participants were recruited from eight geographically contiguous reservations, with a total population of about 3,000 individuals, using a combination of a venue-based method for sampling hard-to-reach populations (Kalton and Anderson, 1986
; Muhib et al., 2001
), as well as a respondent-driven procedure (Heckathorn, 1997
) as previously described (Ehlers et al., 2004a
; Gilder et al., 2004
). The venues for recruitment included: tribal halls and culture centers, health clinics, tribal libraries, and stores on the reservations. A 10–25% rate of refusal was found depending on venue. Refusal rates were higher at tribal libraries and stores than health clinics and tribal halls/culture centers. Transportation from their home to The Scripps Research Institute was provided by the study.
To be included in the study, participants had to be an Indian indigenous to the catchment area, at least 1/16th Native American Heritage (NAH), between the age of 18 and 70 years, and be mobile enough to be transported from his or her home to The Scripps Research Institute (TSRI). The protocol for the study was approved by the Institutional Review Board (IRB) of TSRI, and the Indian Health Council, a tribal review group overseeing health issues for the reservations where recruitment was undertaken.
Potential participants first met individually with research staff to have the study explained and give written informed consent. During a screening period, participants had blood pressure and pulse taken, and completed a questionnaire that was used to gather information on demographics, personal medical history, ethnicity, and drinking history (Schuckit, 1985
). Participants were asked to refrain from alcohol and drug usage for 24 hours prior to the testing. No individuals with detectable breath alcohol levels were included in the study dataset (n=3). During the screening period, the study coordinator also noted whether the participant was agitated, tremulous, or diaphoretic and their data were eliminated from subsequent analyses. Each participant also completed an interview with the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA) and the family history assessment module (FHAM) (Bucholz et al., 1994
), which was used to make substance use disorder and psychiatric disorder diagnoses according to Diagnostic and Statistical Manual (DSM-III-R) (American Psychiatric Association, 1987
) criteria in the probands and their family members (American Psychiatric Association, 1987
). The SSAGA is a semi-structured, poly-diagnostic psychiatric interview that has undergone both reliability and validity testing (Bucholz et al., 1994
; Hesselbrock et al., 1999
). It has been used in another Native American sample (Hesselbrock et al., 2000
). Personnel from the Collaborative Study on the Genetics of Alcoholism (COGA) trained all interviewers. The SSAGA interview includes retrospective lifetime assessments of alcohol use, abuse, and dependence. A research psychiatrist/addiction specialist made all best final diagnoses.
Level of response to alcohol was estimated using a retrospective report instrument the Self-Rating of the Effects of Alcohol (SRE) measure. This instrument asks study participants to retrospectively estimate the number of standard drinks containing ethanol (e.g. the equivalence of 12 oz. of beer, 4 oz. of wine, and 1.5 oz. of 80 proof beverage) that were required for that person to experience four potential effects of the drug: (1) feeling any effects, (2) feeling dizzy/trouble talking, (3) trouble thinking/walking, and (4) falling asleep when you didn’t want to. The instrument also queries an individual to rate these reactions during different time points in a persons life including: (1) the FIRST FIVE TIMES or so that they ever drank, (2) during the most recent 3 months and (3) during the period of heaviest alcohol intake (see Schuckit et al., 1997a
). The score is generated by counting up the number of drinks reported in each time period (FIRST FIVE, last 3 months, heaviest period) and dividing this score by the number of effects (any, dizzy, trouble thinking, falling asleep) endorsed. If a subject did not experience an effect during that time frame then that item is not counted. The analyses here focused on the number of drinks reported for the FIRST FIVE TIMES measure for the 4 effects. Selecting this measure increases the probability that participants refer more uniformly to a similar period in their lives and is most likely to result in a better estimate of “innate” tolerance rather than “acquired” tolerance. Additionally, it has been used previously in a linkage analysis utilizing the COGA dataset (see Schuckit et al., 2001a
). Prior analyses have demonstrated that the relationship between SRE scores to alcohol challenge results remains statistically significant even after controlling for the number of effects of alcohol endorsed by the subjects (see Schuckit et al., 1997a
One hundred and eighty-one pedigrees containing 1600 individuals were used in the genetic analyses. Sixty-six families have only a single individual with phenotype data. All these individuals were included within some analyses to the extent that they contribute information about trait means and variance and the impact of covariates. The family sizes for the remaining families ranged between 4 and 41 subjects (average 12.19 ± 8.19). Eighty-one families were genetically informative. The data includes 142 parent-child, 260 sibling, 53 half sibling, 11 grandparent-grandchild, 235 avuncular, and 240 cousin relative pairs. Only sibling, half-sibling, avuncular and cousin pairs were included as being potentially genetically informative. Several pedigrees contained large numbers of individuals and/or complex loops that could not be analyzed due to the high computational demands required. These pedigrees were thus broken using procedures originally described by Lange and Elston (1975)
, and treated as independent to allow for their inclusion in the linkage analysis.
DNA was isolated from whole blood using an automated DNA extraction procedure, genotyping was done as previously described (Wilhelmsen et al., 2003
). Genotypes were determined for a panel of 791 autosomal microsatellite polymorphisms (Weber and May, 1989
) using fluorescently labeled PCR primers under conditions recommended by the manufacturer (HD5 version 2.0; Applied Biosystems, Foster City, CA). The HD5 panel set has an average marker-to-marker distance of 4.6 cM, and an average heterozygosity of greater than 77% in a Caucasian population. Allele frequencies observed in the unrelated founders were used for linkage analysis. Gender and age accounted for greater than 5% of the phenotypic variance for the phenotype. Therefore, age and gender were included as covariates in the analyses.
Genotypes were determined for 410 subjects. The PREST software program, which assesses degree of allele sharing among relative-pairs, was used to identify potential errors in pedigree structure (McPeek and Sun, 2000
). Six individuals were identified as problematic and removed from further analyses. Pedcheck was then used to detect non-Mendelian inheritance patterns (O’Connell and Weeks, 1998
). When a Mendelian inconsistency was observed, genotypes for the nuclear family at that polymorphism were removed. This resulted in the removal of 772 genotypes. To further reduce errors, the maximum-likelihood error-checking algorithm implemented in Merlin (Abecasis et al., 2002
) was used to identify genotypes that had a probability of less than 0.025 of being correct. A total of 508 genotypes were removed in this step. Ultimately 273,598 genotypes were accepted.
For linkage analysis, a variance components approach was used to calculate multipoint LOD scores at 1 cM intervals across the genome using SOLAR v2.0.4 (Almasy and Blangero, 1998
; S.F.B.R, 2009
). Variance components linkage analysis assumes that phenotypes are normally distributed, and violations of this assumption can result in inflated LOD scores. To protect against this possibility, simulations were conducted in which a single genetic locus was simulated under the null hypothesis of no linkage across 50,000 trials to derive empirical p-values. These p-values were used to determine the significance of the reported LOD scores (Blangero et al., 2000