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Summary Statistics

You can filter the data below or go straight to the results. Descriptions of the various cell types we distribute, such as CPLs and LCLs, can be found here. Note that CPLs are ideal for creating iPSCs. Information on ordering biomaterials can be found here.

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Disease Distributions

Subjects are grouped into distributions according to the way they were ascertained for their respective studies. This should not be confused with clinical diagnoses. Subjects in the Nicotine Dependence distribution, for example, may or may not be diagnosed with Nicotine Dependence. By default, all distributions are used.

Demographics, Biomaterials and Clinical Instruments

Sex:

Age:Between and

Race(s):

Has DNA:

Cell Types:

Cell Types Logic: OR AND

Cell type descriptions can be found here.

Clinical Instrument(s):

Clinical Diagnoses

Multiple Diagnosis Logic*: OR AND

*Example: when OR is selected, if you select both Nicotine and Alcohol dependence you get statistics for the combined set Nicotine-dependent subjects and Alcohol-dependent subjects. When AND is selected, you get statistics for subjects that are both Nicotine-dependent and Alcohol-dependent.

Opioid Dependence:

Cocaine Dependence:

Alcohol Dependence:

Nicotine Dependence:

Cannabis Dependence:

Stimulant Dependence:

Sedative Dependence:

Other Dependence:

Opioid Abuse:

Cocaine Abuse:

Alcohol Abuse:

Cannabis Abuse:

Stimulant Abuse:

Sedative Abuse:

Other Abuse:

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Results

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Breakdown by Disease Distribution

Cell type descriptions (LCLs, CPLs, etc) can be found here.

Distribution Subjects With DNA Plasma LCLs CPLs Whole Blood
Cannabis 1.0 201 201 (100%) 0 ( 0%) 0 ( 0%) 0 ( 0%) 199 (99%)
Cocaine Dependence 3.0 2,443 1,568 (64%) 95 ( 4%) 1,155 (47%) 1,485 (61%) 133 ( 5%)
Nicotine Dependence 11.0 15,593 13,230 (85%) 2,467 (16%) 7,716 (49%) 12,636 (81%) 4,658 (30%)
Opioid Dependence 5.7 7,971 6,556 (82%) 2 ( 0%) 3,189 (40%) 4,240 (53%) 3,860 (48%)
Opioid-Cocaine Dependence 2.1 7,007 5,344 (76%) 0 ( 0%) 2,128 (30%) 4,922 (70%) 2,879 (41%)
Polysubstance Dependence 4.0 4,453 3,465 (78%) 3 ( 0%) 2,004 (45%) 3,365 (76%) 1,814 (41%)
Total 37,668 30,364 (81%) 2,567 ( 7%) 16,192 (43%) 26,648 (71%) 13,543 (36%)

Demographics, DNA and Clinical Instruments

Item Value
Subjects 37,668
With DNA 30,364 (81%)
Instrument: DSM-IV 23,853 (63%)
Instrument: DSM-III-R 1,028 (3%)
Instrument: Unknown 12,787 (34%)
Females / Males / Unknown 17,737 (47%) / 19,880 (53%) / 51 (0%)
Age Average: 39.9, Min: 11, Max: 111
Race: White 18,714 (50%)
Race: African-American 11,192 (30%)
Race: Hispanic 2,097 (6%)
Race: Missing 234 (1%)
Race: American Indian 45 (0%)
Race: Asian 2,030 (5%)
Race: Pac Islander 3 (0%)
Race: Other 3,353 (9%)

Cell Types

Cell type descriptions (LCLs, CPLs, etc) can be found here.

Cell Type Subjects
LCL 16,192 (43%)
CPL 26,648 (71%)
LCL gDNA 15,752 (42%)
WB gDNA 16,420 (44%)
Plasma 2,567 ( 7%)
Whole Blood 13,543 (36%)

Diagnoses

Disease Affected Unaffected Other
Opioid Dependence 8,304 (22%) 13,675 (36%) 15,689 (42%)
Cocaine Dependence 8,318 (22%) 15,135 (40%) 14,215 (38%)
Alcohol Dependence 5,983 (16%) 14,326 (38%) 17,359 (46%)
Nicotine Dependence 9,146 (24%) 6,826 (18%) 21,696 (58%)
Cannabis Dependence 4,512 (12%) 13,421 (36%) 19,735 (52%)
Stimulant Dependence 1,454 ( 4%) 12,335 (33%) 23,879 (63%)
Sedative Dependence 1,063 ( 3%) 12,189 (32%) 24,416 (65%)
Other Drug Dependence 1,035 ( 3%) 14,410 (38%) 22,223 (59%)
Opioid Abuse 1,202 ( 3%) 10,912 (29%) 25,554 (68%)
Cocaine Abuse 1,285 ( 3%) 10,335 (27%) 26,048 (69%)
Alcohol Abuse 2,971 ( 8%) 9,019 (24%) 25,678 (68%)
Cannabis Abuse 2,130 ( 6%) 9,382 (25%) 26,156 (69%)
Stimulant Abuse 278 ( 1%) 8,848 (23%) 28,542 (76%)
Sedative Abuse 324 ( 1%) 8,395 (22%) 28,949 (77%)
Other Drug Abuse 460 ( 1%) 7,843 (21%) 29,365 (78%)

Breakdown by NIDA Studies

Cell type descriptions (LCLs, CPLs, etc) can be found here.

Cannabis Dependence
Study Name PI Subjects With DNA Plasma LCLs CPLs Whole Blood
32 Achieving Cannabis Cessation-Evaluation of N-Acetylcysteine (ACCENT); CTN-0053 Kevin Gray 201 201 (100%) 0 ( 0%) 0 ( 0%) 0 ( 0%) 199 (99%)
Total 201 201 (100%) 0 ( 0%) 0 ( 0%) 0 ( 0%) 199 (99%)
Cocaine Dependence
Study Name PI Subjects With DNA Plasma LCLs CPLs Whole Blood
7 An Introduction to the Family Study of Cocaine Laura Bierut 1,914 1,049 (55%) 95 ( 5%) 852 (45%) 990 (52%) 103 ( 5%)
13 Genetics of Cocaine Induced Psychosis Joseph F. Cubells 249 241 (97%) 0 ( 0%) 239 (96%) 224 (90%) 1 ( 0%)
29 Genetics Protocol of the Cocaine Use Reduction with Buprenorphine (CURB) Study; CTN-0048 David A. Nielsen 280 278 (99%) 0 ( 0%) 64 (23%) 271 (97%) 29 (10%)
Total 2,443 1,568 (64%) 95 ( 4%) 1,155 (47%) 1,485 (61%) 133 ( 5%)
Nicotine Dependence
Study Name PI Subjects With DNA Plasma LCLs CPLs Whole Blood
NicSNP The NicSNP Study Laura Bierut 1,927 1,927 (100%) 515 (27%) 1,340 (70%) 1,878 (97%) 772 (40%)
2 Mapping Susceptibility Genes for Nicotine Dependence Ming D. Li 2,803 1,962 (70%) 0 ( 0%) 1,961 (70%) 1,837 (66%) 148 ( 5%)
6 The Genetics of Vulnerability to Nicotine Pamela Madden 3,446 2,344 (68%) 0 ( 0%) 2,330 (68%) 2,156 (63%) 30 ( 1%)
9 Differentiation of Phenotypes for Smoking: Administrative Supplement to Join NIDA Genetics Consortium Ovide Pomerleau 1,565 1,540 (98%) 0 ( 0%) 607 (39%) 1,502 (96%) 887 (57%)
10 Pharmacokinetics of Nicotine in Twins Gary Swan 124 62 (50%) 0 ( 0%) 62 (50%) 60 (48%) 0 ( 0%)
15 Nicotine Dependence Laura Bierut 2,146 1,813 (84%) 876 (41%) 854 (40%) 1,760 (82%) 1,131 (53%)
16 Nicotine Dependence Mark Leppert 917 917 (100%) 2 ( 0%) 359 (39%) 821 (90%) 535 (58%)
27 The Genetic Study of Nicotine Dependence in African Americans (AAND) Laura Bierut 1,792 1,792 (100%) 206 (11%) 194 (11%) 1,753 (98%) 1,134 (63%)
35 Genetically Informative Smoking Cessation Trial Li-Shiun Chen 873 873 (100%) 868 (99%) 9 ( 1%) 869 (100%) 21 ( 2%)
Total 15,593 13,230 (85%) 2,467 (16%) 7,716 (49%) 12,636 (81%) 4,658 (30%)
Opioid Dependence
Study Name PI Subjects With DNA Plasma LCLs CPLs Whole Blood
3 Molecular Genetics of Heroin Dependence in China Ming Tsuang 1,929 1,232 (64%) 0 ( 0%) 1,097 (57%) 3 ( 0%) 222 (12%)
5 Addictions, Genotypes, Polymorphisms, and Function Mary Jeanne Kreek 1,751 1,751 (100%) 2 ( 0%) 768 (44%) 1,708 (98%) 1,012 (58%)
14 Genome-Wide Analysis for Addiction Susceptibility Genes Herb Lachman 1,405 693 (49%) 0 ( 0%) 598 (43%) 640 (46%) 116 ( 8%)
17 Opioid Dependence Wade Berrettini 204 200 (98%) 0 ( 0%) 70 (34%) 191 (94%) 99 (49%)
18 Opioid Dependence: Candidate Genes and G x E Effects Elliot Nelson 1,896 1,895 (100%) 0 ( 0%) 500 (26%) 954 (50%) 1,627 (86%)
24 START Pharmacogenetics: Exploratory Genetic Studies in Starting Treatment with Agonist Replacement Therapies (START) Wade Berrettini 786 785 (100%) 0 ( 0%) 156 (20%) 744 (95%) 784 (100%)
Total 7,971 6,556 (82%) 2 ( 0%) 3,189 (40%) 4,240 (53%) 3,860 (48%)
Opioid-Cocaine Dependence
Study Name PI Subjects With DNA Plasma LCLs CPLs Whole Blood
1 Genetics of Opioid Dependence Joel Gelernter 6,511 4,848 (74%) 0 ( 0%) 2,118 (33%) 4,705 (72%) 2,785 (43%)
20 Innovative Approaches for Cocaine Pharmacotherapy Henry Kranzler 496 496 (100%) 0 ( 0%) 10 ( 2%) 217 (44%) 94 (19%)
Total 7,007 5,344 (76%) 0 ( 0%) 2,128 (30%) 4,922 (70%) 2,879 (41%)
Polysubstance Dependence
Study Name PI Subjects With DNA Plasma LCLs CPLs Whole Blood
11 Adolescent Drug Dependence John Hewitt 2,403 1,589 (66%) 1 ( 0%) 1,084 (45%) 1,521 (63%) 502 (21%)
12 Substance Abuse and the Dopamine System Genes Michael M. Yanyukov 600 470 (78%) 0 ( 0%) 406 (68%) 449 (75%) 0 ( 0%)
19 Epidemiological Study of Substance Abuse Rob Philibert 562 520 (93%) 1 ( 0%) 485 (86%) 510 (91%) 430 (77%)
23 Substance Use Disorder Liability: Candidate Gene System Michael M. Vanyukov 888 886 (100%) 1 ( 0%) 29 ( 3%) 885 (100%) 882 (99%)
Total 4,453 3,465 (78%) 3 ( 0%) 2,004 (45%) 3,365 (76%) 1,814 (41%)

cell_file version: 2023-11-14 #2