Supplement 2. Demographic Characteristics of the PEG Study Population
Supplement 2. Demographic characteristics of the PEG study population
Study / HLA (Kannarkat et al, 2015,[30]) / PON1 (Nayaran et al, 2013,[15]) / NOS1 (Paul et al, 2015,[25]) / ALDH2 (Fitzmaurice et al, 2014,[9]) / DAT (Ritz et al, 2009,[19]) / SKP1 (Rhodes et al, 2013,[10]) / PON1 (Lee et al, 2013,[23])Variable
n (%) unless otherwise noted / Cases N=465 / Controls N=497 / Cases N=357 / Controls N=807 / Cases N=357 / Controls N=495 / Cases N=353 / Controls N=518 / Cases N=324 / Controls N=334 / Cases N=287 / Controls N=453 / Cases N=287 / Controls N=440
Age, mean ± sd / 69.4 ± 9.9 / 67.4 ± 11.7 / 68.3 ± 10.2 / 66.2 ± 11.6 / 68.3 ± 10.2 / 66.7 ± 12.3 / 68.3 ± 10.2 / 67 ± 12.2 / 70.0 ± 10.4 / 68.5 ± 12.5 / 69.0 ± 10.5 / 67.6 ± 12 / 69.0 ± 10.5 / 67.6 ± 11.9
Gender
Male / 289 (0.52) / 262 (0.48) / 205 (0.57) / 371 (0.46) / 204 (0.57) / 243 (0.49) / 203 (0.58) / 251 (0.49) / 179 (0.55) / 168 (0.50) / 161 (0.56) / 222 (0.49) / 161 (0.56) / 217 (0.49)
Smoking Status
Never / 253 (0.54) / 226 (0.46) / 187 (0.52) / 389 (0.48) / 188 (0.53) / 227 (0.46) / 186 (0.53) / 246 (0.48) / 174 (0.54) / 145 (0.43) / 158 (0.55) / 208 (0.46) / 158 (0.55) / 206 (0.47)
Ever / 212 (0.46) / 271 (0.54) / 170 (0.48) / 418 (0.52) / 169 (0.47) / 268 (0.54) / 167 (0.47) / 272 (0.52) / 150 (0.46) / 189 (0.57) / 129 (0.45) / 245 (0.54) / 129 (0.45) / 234 (0.53)
First Degree Relative with PD
Yes / 76 (0.16) / 47 (0.09) / 52 (0.15) / 65 (0.08) / 53 (0.15) / 45 (0.09) / 53 (0.15) / 43 (0.08) / 47 (0.14) / 35 (0.11) / 41 (0.14) / 41 (0.09) / 41 (0.14) / 41 (0.09)
European ancestry
Yes / 465 (1.0) / 497 (1.0) / 287 (0.80) / 564 (0.70) / 288 (0.81) / 441 (0.89) / 285 (0.81) / 421 (0.81) / 264 (0.82) / 268 (0.80) / 287 (1.0) / 453 (1.0) / 287 (1.0) / 440 (1.0)
No / n.a. / n.a. / 70 (0.20) / 242 (0.30) / 69 (0.19) / 54 (0.11) / 68 (0.19) / 97 (0.19) / 60 (0.18) / 66 (0.20) / n.a. / n.a. / n.a. / n.a.
Education
< 12 years / 38 (0.08) / 35 (0.07) / 66 (0.19) / 116 (0.14) / 65 (0.18) / 43 (0.09) / 64 (0.18) / 55 (0.11) / 58 (0.18) / 34 (0.10) / 32 (0.11) / 29 (0.06) / 32 (0.11) / 26 (0.06)
= 12 years / 121 (0.26) / 103 (0.21) / 96 (0.27) / 166 (0.21) / 95 (0.27) / 101 (0.20) / 94 (0.27) / 104 (0.20) / 89 (0.28) / 70 (0.21) / 84 (0.29) / 91 (0.20) / 84 (0.29) / 87 (0.20)
> 12 years / 306 (0.66) / 306 (0.66) / 195 (0.54) / 525 (0.65) / 197 (0.55) / 351 (0.71) / 195 (0.55) / 358 (0.69) / 177 (0.55) / 230 (0.69) / 171 (0.60) / 333 (0.74) / 171 (0.60) / 317 (0.74)
Supplement 2 References:
1 Jacob EL, Gatto NM, Thompson A, et al. Occurrence of depression and anxiety prior to Parkinson’s disease. Parkinsonism Relat Disord 2010;16:576–81.
2 Kang GA, Bronstein JM, Masterman DL, et al.Clinical characteristics in early Parkinson’s disease in a central California population-based study. Mov Disord 2005;20:1133–42.
3 Costello S, Cockburn M, Bronstein J, et al. Parkinson’s disease and residential exposure to maneb and paraquat from agricultural applications in the central valley of California. Am J Epidemiol 2009;169:919–26.
4 Hughes AJ, Ben-Shlomo Y, Daniel SE, et al. What features improve the accuracy of clinical diagnosis in Parkinson’s disease: a clinicopathologic study. Neurology 1992;42:1142–6.
5 Langston JW, Widner H, Goetz CG, et al. Core assessment program for intracerebral transplantations (CAPIT). Mov Disord 1992;7:2–13.
6 Ritz B, Costello S. Geographic model and biomarker-derived measures of pesticide exposure and Parkinson’s disease. Ann N Y Acad Sci 2006;1076:378–87.
7 Goldberg DW, Wilson JP, Knoblock CA, et al. An effective and efficient approach for manually improving geocoded data. Int J Health Geogr 2008;7:60.
8 Rull RP, Ritz B. Historical pesticide exposure in California using pesticide use reports and land-use surveys: an assessment of misclassification error and bias. Environ Health Perspect 2003;111:1582–9.
9 Fitzmaurice AG, Rhodes SL, Cockburn M, et al. Aldehyde dehydrogenase variation enhances effect of pesticides associated with Parkinson disease. Neurology 2014;82:419–26.
10 Rhodes SL, Fitzmaurice AG, Cockburn M, et al. Pesticides that inhibit the ubiquitin-proteasome system: effect measure modification by genetic variation in SKP1 in Parkinson׳s disease. Environ Res 2013;126:1–8.
11 Corsini E, Sokooti M, Galli CL, et al. Pesticide induced immunotoxicity in humans: a comprehensive review of the existing evidence. Toxicology 2013;307:123–35.
12 Public Use Microdata Series (IPUMS-USA) Occupation Code System. 2000. (accessed 1 Jan2010).
13 Young HA, Mills PK, Riordan D, et al. Use of a crop and job specific exposure matrix for estimating cumulative exposure to triazine herbicides among females in a case-control study in the Central Valley of California. Occup Environ Med 2004;61:945–51.
14 Liew Z, Wang A, Bronstein J, et al. Job exposure matrix (JEM)-derived estimates of lifetime occupational pesticide exposure and the risk of Parkinson’s disease. Arch Environ Occup Health 2014;69:241–51.
15 Narayan S, Liew Z, Paul K, et al. Household organophosphorus pesticide use and Parkinson’s disease. Int J Epidemiol 2013;42:1476–85.
16 California Department of Pesticide Regulation. Product/Label Database. 2010. (accessed 13 Aug2010).
17 Kegley S, Hill B, Orme S, et al. Pesticide Action Network PAN Pesticides Database – Chemicals. 2000. (accessed 3 Nov2010).
18 Wood A. Compendium of pesticide common names. (accessed 1 Jan2010).
19 Ritz BR, Manthripragada AD, Costello S, et al. Dopamine transporter genetic variants and pesticides in Parkinson’s disease. Environ Health Perspect 2009;117:964–9.
20 Kelada SN, Costa-Mallen P, Checkoway H, et al. Dopamine transporter (SLC6A3) 5’ region haplotypes significantly affect transcriptional activity in vitro but are not associated with Parkinson's disease. Pharmacogenet Genomics 2005;15:659–68.
21 Kelada SNP, Checkoway H, Kardia SLR, et al. 5′ and 3′ region variability in the dopamine transporter gene (SLC6A3), pesticide exposure and Parkinson’s disease risk: A hypothesis-generating study. Hum Mol Genet 2006;15:3055–62. doi:10.1093/hmg/ddl247
22 Vandenbergh DJ, Persico AM, Hawkins AL, et al.Human dopamine transporter gene (DAT1) maps to chromosome 5p15.3 and displays a VNTR. Genomics 1992;14:1104–6.
23 Lee P-C, Rhodes SL, Sinsheimer JS, et al.Functional paraoxonase 1 variants modify the risk of Parkinson’s disease due to organophosphate exposure. Environ Int 2013;56:42–7.
24 Manthripragada AD, Costello S, Cockburn MG, et al. Paraoxonase 1, agricultural organophosphate exposure, and Parkinson disease. Epidemiology 2010;21:87–94.
25 Paul KC, Sinsheimer JS, Rhodes SL, et al. Organophosphate Pesticide Exposures, Nitric Oxide Synthase Gene Variants, and Gene-Pesticide Interactions in a Case-Control Study of Parkinson’s Disease, California (USA). Environ Health Perspect Published Online First: 2015. doi:10.1289/ehp.1408976
26 Tobler AR, Short S, Andersen MR, et al. The SNPlex genotyping system: a flexible and scalable platform for SNP genotyping. J Biomol Tech 2005;16:398–406.
27 Seltman H, Roeder K, Devlin B. Evolutionary-based association analysis using haplotype data. Genet Epidemiol 2003;25:48–58.
28 Barrett JC, Fry B, Maller J, et al. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 2005;21:263–5. doi:10.1093/bioinformatics/bth457
29 Ragland M, Hutter C, Zabetian C, et al.Association Between the Ubiquitin Carboxyl-Terminal Esterase L1 Gene (UCHL1) S18Y Variant and Parkinson’s Disease: A HuGE Review and Meta-Analysis. Am J Epidemiol 2009;170:1344–57.
30 Kannarkat GT, Cook DA, Lee J-K, et al.Common genetic variant association with altered HLA expression, synergy with pyrethroid exposure, and risk for Parkinson’s disease: an observational and case–control study. npj Park Dis 2015;1:15002.
31 Narayan S, Sinsheimer JS, Paul KC, et al. Genetic variability in ABCB1, occupational pesticide exposure, and Parkinson’s disease. Environ Res 2015;Accepted (in press).