The <i>P</i>‐value illusion: How to improve (psychiatric) genetic studies

Copy number variants (CNVs) are a recently recognized class of human germ line polymorphisms and are associated with a variety of human diseases, including cancer. Because of the strong genetic influence on prostate cancer, we sought to identify functionally active CNVs associated with susceptibility of this cancer type. We queried low-frequency biallelic CNVs from 1,903 men of Caucasian origin enrolled in the Tyrol Prostate Specific Antigen Screening Cohort and discovered two CNVs strongly associated with prostate cancer risk. The first risk locus (P = 7.7 × 10 −4 , odds ratio = 2.78) maps to 15q21.3 and overlaps a noncoding enhancer element that contains multiple activator protein 1 (AP-1) transcription factor binding sites. Chromosome conformation capture (Hi-C) data suggested direct cis-interactions with distant genes. The second risk locus (P = 2.6 × 10 −3 , odds ratio = 4.8) maps to the α-1,3-mannosyl-glycoprotein 4-β-N-acetylglucosaminyltransferase C (MGAT4C) gene on 12q21.31. In vitro cell-line assays found this gene to significantly modulate cell proliferation and migration in both benign and cancer prostate cells. Furthermore, MGAT4C was significantly overexpressed in metastatic versus localized prostate cancer. These two risk associations were replicated in an independent PSA-screened cohort of 800 men (15q21.3, combined P = 0.006; 12q21.31, combined P = 0.026). These findings establish noncoding and coding germ line CNVs as significant risk factors for prostate cancer susceptibility and implicate their role in disease development and progression.cancer genetics | functionally active DNA loci | cancer predisposition | metabolism | chromosome looping

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“…rate is comparable to other recent studies (15,16) and could be attributed to cohort and disease heterogeneity (17,18).…”

Section: Resultssupporting

confidence: 90%

Identification of functionally active, low frequency copy number variants at 15q21.3 and 12q21.31 associated with prostate cancer risk

Demichelis

Setlur

Banerjee³

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

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“…Using a genomic control method, we found no evidence of population stratification. While increasing the sample size and determining Bonferroni-corrected p values can be helpful to address multiple comparisons, these approaches alone may not be enough to address the complexity and heterogeneity of an illness like CFS [20] . Validating these findings will require replication of SNP and gene expression analysis in a replication study in a larger independent population.…”

Section: Discussionmentioning

confidence: 99%

Convergent Genomic Studies Identify Association of GRIK2 and NPAS2 with Chronic Fatigue Syndrome

et al. 2011

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Background: There is no consistent evidence of specific gene(s) or molecular pathways that contribute to the pathogenesis, therapeutic intervention or diagnosis of chronic fatigue syndrome (CFS). While multiple studies support a role for genetic variation in CFS, genome-wide efforts to identify associated loci remain unexplored. We employed a novel convergent functional genomics approach that incorporates the findings from single-nucleotide polymorphism (SNP) and mRNA expression studies to identify associations between CFS and novel candidate genes for further investigation. Methods: We evaluated 116,204 SNPs in 40 CFS and 40 nonfatigued control subjects along with mRNA expression of 20,160 genes in a subset of these subjects (35 CFS subjects and 27 controls) derived from a population-based study. Results: Sixty-five SNPs were nominally associated with CFS (p < 0.001), and 165 genes were differentially expressed (≧4-fold; p ≤ 0.05) in peripheral blood mononuclear cells of CFS subjects. Two genes, glutamate receptor, ionotropic, kinase 2 (GRIK2) and neuronal PAS domain protein 2 (NPAS2), were identified by both SNP and gene expression analyses. Subjects with the G allele of rs2247215 (GRIK2) were more likely to have CFS (p = 0.0005), and CFS subjects showed decreased GRIK2 expression (10-fold; p = 0.015). Subjects with the T allele of rs356653 (NPAS2) were more likely to have CFS (p = 0.0007), and NPAS2 expression was increased (10-fold; p = 0.027) in those with CFS. Conclusion: Using an integrated genomic strategy, this study suggests a possible role for genes involved in glutamatergic neurotransmission and circadian rhythm in CFS and supports further study of novel candidate genes in independent populations of CFS subjects.

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“…In addition, there is a genetic overlap with other psychiatric disorders, especially bipolar disorder. However, use of the case-case model in genetic analyses helps to reduce clinical heterogeneity and environmental differences between mental disorder groups [33]. The case-case model may represent a narrow subgroup of psychosis patients, more biologically correlated and hence more related to susceptibility genes than psychosis patients in general [34].…”

Section: Strengths and Limitationsmentioning

confidence: 99%

Genes Associated with Increased Fasting Glucose in Patients with Schizophrenia Spectrum Disorders

Hukic

Olsson²,

Hilding³

et al. 2016

J Diabetes Metab

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The P‐value illusion: How to improve (psychiatric) genetic studies

Cited by 23 publications

References 19 publications

Identification of functionally active, low frequency copy number variants at 15q21.3 and 12q21.31 associated with prostate cancer risk

Identification of functionally active, low frequency copy number variants at 15q21.3 and 12q21.31 associated with prostate cancer risk

Convergent Genomic Studies Identify Association of GRIK2 and NPAS2 with Chronic Fatigue Syndrome

Genes Associated with Increased Fasting Glucose in Patients with Schizophrenia Spectrum Disorders

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