Multi-environment gene interactions linked to the interplay between polysubstance dependence and suicidality.

paper Cited Public

Authors: Polimanti, Renato; Levey, Daniel F; Pathak, Gita A; Wendt, Frank R; Nunez, Yaira Z; Ursano, Robert J; Kessler, Ronald C; Kranzler, Henry R; Stein, Murray B; Gelernter, Joel
Year: 2021
Journal: Translational psychiatry
PMID: 33431810
DOI: 10.1038/s41398-020-01153-1
PMCID: PMC7801457

Fig. 1

Substance dependence (SD) and suicidality in Yale-Penn participants.Association of DSM-IV SD diagnoses (left panel) or polysubstance dependence severity (i.e., number of comorbid DSM-IV SD diagnosis; right panel) with suicidal ideation, persistent ideation, planning, and attempt.

LLM interpretation

This figure consists of two forest plots showing the association between substance dependence (SD) and various measures of suicidality (ideation, persistent ideation, planning, and attempt). The left panel displays odds ratios (OR) and 95% confidence intervals (CI) for specific DSM-IV SD diagnoses, while the right panel shows the association based on the number of comorbid SD diagnoses (N=1 to 5). In both panels, most ORs are above 1.0, with the strongest associations generally observed for alcohol dependence and higher numbers of comorbid SD diagnoses.

Fig. 2

Gene-based Manhattan plots generated from the multivariate GEWIS of suicide ideation.Bottom panel: interactive effects where persistent genetic and additive environment effects are accounted for in the null model; Top panel: association effects accounting for the heterogeneous effect size due to the interactive effects). Red dashed line represents the significance threshold accounting for the gene-based Bonferroni multiple testing correction.

LLM interpretation

This figure consists of two gene-based Manhattan plots showing the association between genetic loci and suicide ideation across 22 chromosomes. The y-axis represents the $-\log_{10}$ P-value, and a red dashed line indicates the Bonferroni-corrected significance threshold. In both the top (association effects) and bottom (interactive effects) panels, several significant peaks are visible on chromosome 16, with specific genes labeled including *LCAT*, *TSNAXIP1*, *CENPT*, and *PARD6A*.

Fig. 3

Regional Manhattan plot of the lead variant rs8052287.This was identified in the gene-based multivariate GEWIS of suicide ideation (Yale-Penn participants of European descent) Functional annotation derived from CADD (Combined Annotation Dependent Depletion) and RegulomeDB scores and 15-core chromatin state information across 13 brain tissues is included below. CADD scores > 20 corresponds to top-1% of pathogenicity across the human genome. RegulomeDB Score = 1 (f to a) corresponds to variants located within a transcription factor binding that shows eQTL activity.

LLM interpretation

This figure presents a regional Manhattan plot for the lead variant rs8052287 on Chromosome 16, with the y-axis showing $-\log_{10}$ P-values and points color-coded by linkage disequilibrium ($r^2$). Below the plot, a genomic map identifies mapped genes, categorized as non-protein coding (grey) or non-mapped protein coding (blue). The bottom panels provide functional annotations for the variants, including CADD scores, RegulomeDB scores, and a multi-colored heatmap representing chromatin states across 13 brain tissues.

#	Section	Preview
0	Introduction	Individuals with substance dependence diagnoses (SDs) are a population with high suicide risk.…
1	Introduction	Recently, genome-wide association studies (GWAS) of suicidality have been conducted in large…
2	Introduction	(SP), and suicide attempt (SA). Subsequently, we conducted a discovery GEWIS to verify whether SDs…
3	Materials and methods — Study populations	Yale-Penn participants were recruited for studies of the genetics of drug or alcohol dependence in…
4	Materials and methods — Study populations	least 7 days in a row? [Yes/No]”; SP “Did you have a plan? [Yes/No]”; and SA “Have you ever…
5	Materials and methods — Study populations	our previous studies14–16. Briefly, Individuals and SNPs with genotype call rates <98%, and SNPs…
6	Materials and methods — Study populations	The Army STARRS (Study to Assess Risk and Resilience in Servicemembers) participants included…
7	Materials and methods — Study populations	of SI (“Did you ever in your life have thoughts of killing yourself? [Yes/No]” OR “Did you…
8	Materials and methods — Study populations	previously23. Briefly, the quality control parameters applied included SNP missingness <0.05,…
9	Materials and methods — Study populations	Table 1 reports the characteristics of the Yale-Penn and Army STARRS participants investigated in…
10	Materials and methods — Data analysis — Phenotypic associations	We used multivariate logistic regression models to test the association of SDs with suicidality…
11	Materials and methods — Data analysis — Genome-wide Gene-by-SD interaction analysis of SI	In the Yale–Penn cohort, we conducted a multivariate GEWIS considering unrelated participants with…
12	Materials and methods — Data analysis — Genome-wide Gene-by-SD interaction analysis of SI	We used the StructLMM approach to analyze whether DSM-IV criterion counts of AD, CaD, CoD, OD, and…
13	Materials and methods — Data analysis — Genome-wide Gene-by-SD interaction analysis of SI	alternate vs. null models, respectively. Specifically, the BFs were calculated between the full…
14	Materials and methods — Data analysis — Genome-wide Gene-by-SD interaction analysis of SI	To increase the discovery power of the analysis conducted in the Yale-Penn cohort, we used the…
15	Materials and methods — Data analysis — Replication analysis	The Army STARRS cohort (11,235 participants of genetically-confirmed European descent; see Study…
16	Materials and methods — Data analysis — Polygenic risk score analysis	We leveraged the Psychiatric Genomic Consortium (PGC) GWAS of major depression (MD)33 to generate…
17	Materials and methods — Data analysis — Polygenic risk score analysis	tested. The PRS were calculated after using P-value-informed clumping with a LD cut-off of R2 = 0.3…
18	Results — Phenotypic associations	To identify effects accounting for the comorbidity among the SDs tested in the Yale-Penn cohort, AD,…
19	Results — Phenotypic associations	SI (OR = 1.62; 95% CI = 1.47–1.80) and negative association with SA (OR = 0.84; 95% CI =…

Name	Type
23andMe	cohort
ACD local	gene
African American	cohort
African-Americans	cohort
age	phenotype
alcohol	phenotype
Alcohol and cocaine use disorder local	phenotype
Alcohol and marijuana use disorder local	phenotype
alcohol dependence	phenotype
Alcohol Use Disorder	phenotype
amphetamine	drug
Amphetamine use disorder	phenotype
anthropometric traits	phenotype
anxiety	phenotype
Army STARRS	cohort
Army STARRS participants local	cohort
Attempt local	phenotype
Been in serious accident believed to be life-threatening local	phenotype
brain tissue	anatomy
C16orf86 local	gene
CADD	drug
cannabis dependence	phenotype
Cannabis Dependence local	drug
cannabis use	phenotype
cannabis use disorder	phenotype
CARMIL2 local	gene
caudate nucleus	anatomy
CENPT local	gene
central nervous system	anatomy
cerebellar hemisphere	anatomy
cerebellum	anatomy
cigarettes	phenotype
cocaine	phenotype
cocaine dependence local	drug
cocaine use disorder	phenotype
CoD criterion counts local	phenotype
Combined Substance Use Disorder local	phenotype
controls	cohort
co-occurrence of multiple SD diagnoses local	phenotype
cortex	anatomy
cotinine	drug
depression	phenotype
DSM‑IV mental disorders local	phenotype
DUS2 local	gene
European ancestry	cohort
European population	cohort
fatigue	phenotype
FHOD1 local	gene
frontal cortex BA9 local	anatomy
GTEx local	drug
GWAS Atlas local	drug
height	phenotype
hematological parameters local	phenotype
HGF local	gene
HSD11B2	gene
hypothyroidism	phenotype
Ideation local	phenotype
illicit drug use	phenotype
Illumina Exome array local	drug
Illumina OmniExpress	drug
Illumina PsychChip array local	drug
KCTD19 local	gene
LCAT local	gene
life‑threatening traumatic events local	phenotype
loneliness	phenotype
long-term opioid users local	cohort
LRRC36 local	gene
MAGMA	drug
major depressive disorder	phenotype
male hair loss local	phenotype
male hair loss pattern local	phenotype
marijuana	phenotype
MD	phenotype
MD PRS local	variant
mean corpuscular hemoglobin local	phenotype
mood disorders	phenotype
mood swings	phenotype
National Survey of Drug Use and Health (NSDUH) cohort local	cohort
ND criterion counts local	phenotype
New Soldier Study local	cohort
nicotine	drug
nicotine dependence	phenotype
nucleus accumbens	anatomy
OD criterion counts local	phenotype
opioid	drug
opioid dependence local	drug
opioid dependence	phenotype
Painkiller local	drug
Painkiller use disorder local	phenotype
PARD6A local	gene
Persistent Ideation local	phenotype
persistent SI local	phenotype
Persistent suicidal ideation local	phenotype
Persistent Suicidal Ideation local	phenotype
PGC	cohort
PGC MD cohort local	cohort
planning	phenotype
polygenic risk score	cohort
polysubstance dependence	phenotype
Polysubstance dependence local	drug
Polysubstance Dependence Severity local	phenotype
Pre-Post Deployment Study local	cohort
Psychiatric Genomic Consortium local	cohort
RANBP10 local	gene
RegulomeDB	drug
rs62620177 local	variant
rs8052287 local	variant
SA	phenotype
SD diagnoses local	phenotype
SD-related traits local	phenotype
sedative dependence	phenotype
sedatives	drug
Self-reported racial/ethnic groups local	phenotype
sex	phenotype
SI outcome local	phenotype
SP	phenotype
StructLMM local	drug
Substance dependence (SD) local	phenotype
Substance Dependence (SDs) local	phenotype
substance use	phenotype
Substance use disorder combined local	phenotype
suicidality spectrum local	phenotype
suicide	phenotype
suicide risk	phenotype
thyroid autoimmunity local	phenotype
thyroid function local	phenotype
thyroid-stimulating hormone local	drug
thyroid storm local	phenotype
thyrotropin-releasing hormone local	drug
TSNAXIP1 local	gene
UK Biobank	cohort
Veterans Health Administration (VHA) cohort local	cohort
Yale-Penn	cohort
Yale-Penn African descent cohort local	cohort
Yale-Penn cohort	cohort
Yale–Penn cohort	cohort
Yale-Penn participants of European descent local	cohort
ZDHHC1 local	gene

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In this knowledge base

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External

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