Genetic associations and expression of extra-short isoforms of disrupted-in-schizophrenia 1 in a neurocognitive subgroup of schizophrenia

Almost all complex disorders have manifested epidemiological and clinical sex disparities which might partially arise from sex-specific genetic mechanisms. Addressing such differences can be important from a precision medicine perspective which aims to make medical interventions more personalized and effective. We investigated sex-specific genetic associations with colorectal (CRCa) and lung (LCa) cancers using genome-wide single-nucleotide polymorphisms (SNPs) data from three independent datasets. The genome-wide association analyses revealed that 33 SNPs were associated with CRCa/LCa at P < 5.0 × 10−6 neither males or females. Of these, 26 SNPs had sex-specific effects as their effect sizes were statistically different between the two sexes at a Bonferroni-adjusted significance level of 0.0015. None had proxy SNPs within their ±1 Mb regions and the closest genes to 32 SNPs were not previously associated with the corresponding cancers. The pathway enrichment analyses demonstrated the associations of 35 pathways with CRCa or LCa which were mostly implicated in immune system responses, cell cycle, and chromosome stability. The significant pathways were mostly enriched in either males or females. Our findings provided novel insights into the potential sex-specific genetic heterogeneity of CRCa and LCa at SNP and pathway levels.

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ANCA Status or Clinical Phenotype — What Counts More?

Current Rheumatology Reports ◽

10.1007/s11926-021-01002-0 ◽

2021 ◽

Vol 23 (6) ◽

Author(s):

Martin Windpessl ◽

Erica L. Bettac ◽

Philipp Gauckler ◽

Jae Il Shin ◽

Duvuru Geetha ◽

...

Keyword(s):

Clinical Trials ◽

Granulomatosis With Polyangiitis ◽

Clinical Phenotype ◽

Antineutrophil Cytoplasmic Antibody ◽

Cardiovascular Death ◽

Genetic Associations ◽

Ongoing Debate ◽

The Past ◽

Anca Associated Vasculitis

Abstract Purpose of Review There is ongoing debate concerning the classification of antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis. That is, whether classification should be based on the serotype (proteinase 3 (PR3)- or myeloperoxidase (MPO)-ANCA) or on the clinical phenotype (granulomatosis with polyangiitis (GPA) or microscopic polyangiitis (MPA)). To add clarity, this review focused on integration of the most recent literature. Recent Findings Large clinical trials have provided evidence that a serology-based risk assessment for relapses is more predictive than distinction based on the phenotype. Research conducted in the past decade indicated that a serology-based approach more closely resembles the genetic associations, the clinical presentation (i.e., lung involvement), biomarker biology, treatment response, and is also predicting comorbidities (such as cardiovascular death). Summary Our review highlights that a serology-based approach could replace a phenotype-based approach to classify ANCA-associated vasculitides. In future, clinical trials and observational studies will presumably focus on this distinction and, as such, translate into a “personalized medicine.”

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Penalized partial least squares for pleiotropy

BMC Bioinformatics ◽

10.1186/s12859-021-03968-1 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Camilo Broc ◽

Therese Truong ◽

Benoit Liquet

Keyword(s):

Least Squares ◽

Partial Least Squares ◽

Association Studies ◽

A Priori ◽

Simulated Data ◽

Real Data ◽

Genome Wide Association Studies ◽

Genetic Associations ◽

Multiple Traits ◽

Application Fields

Abstract Background The increasing number of genome-wide association studies (GWAS) has revealed several loci that are associated to multiple distinct phenotypes, suggesting the existence of pleiotropic effects. Highlighting these cross-phenotype genetic associations could help to identify and understand common biological mechanisms underlying some diseases. Common approaches test the association between genetic variants and multiple traits at the SNP level. In this paper, we propose a novel gene- and a pathway-level approach in the case where several independent GWAS on independent traits are available. The method is based on a generalization of the sparse group Partial Least Squares (sgPLS) to take into account groups of variables, and a Lasso penalization that links all independent data sets. This method, called joint-sgPLS, is able to convincingly detect signal at the variable level and at the group level. Results Our method has the advantage to propose a global readable model while coping with the architecture of data. It can outperform traditional methods and provides a wider insight in terms of a priori information. We compared the performance of the proposed method to other benchmark methods on simulated data and gave an example of application on real data with the aim to highlight common susceptibility variants to breast and thyroid cancers. Conclusion The joint-sgPLS shows interesting properties for detecting a signal. As an extension of the PLS, the method is suited for data with a large number of variables. The choice of Lasso penalization copes with architectures of groups of variables and observations sets. Furthermore, although the method has been applied to a genetic study, its formulation is adapted to any data with high number of variables and an exposed a priori architecture in other application fields.

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Genome-wide association analysis of metabolic syndrome quantitative traits in the GENNID multiethnic family study

Diabetology & Metabolic Syndrome ◽

10.1186/s13098-021-00670-3 ◽

2021 ◽

Vol 13 (1) ◽

Author(s):

Jia Y. Wan ◽

Deborah L. Goodman ◽

Emileigh L. Willems ◽

Alexis R. Freedland ◽

Trina M. Norden-Krichmar ◽

...

Keyword(s):

Blood Pressure ◽

Metabolic Syndrome ◽

Family Study ◽

Genome Wide Association ◽

European American ◽

Japanese American ◽

Genetic Associations ◽

Chromosome 11 ◽

Genome Wide ◽

American Families

Abstract Background To identify genetic associations of quantitative metabolic syndrome (MetS) traits and characterize heterogeneity across ethnic groups. Methods Data was collected from GENetics of Noninsulin dependent Diabetes Mellitus (GENNID), a multiethnic resource of Type 2 diabetic families and included 1520 subjects in 259 African-American, European-American, Japanese-Americans, and Mexican-American families. We focused on eight MetS traits: weight, waist circumference, systolic and diastolic blood pressure, high-density lipoprotein, triglycerides, fasting glucose, and insulin. Using genotyped and imputed data from Illumina’s Multiethnic array, we conducted genome-wide association analyses with linear mixed models for all ethnicities, except for the smaller Japanese-American group, where we used additive genetic models with gene-dropping. Results Findings included ethnic-specific genetic associations and heterogeneity across ethnicities. Most significant associations were outside our candidate linkage regions and were coincident within a gene or intergenic region, with two exceptions in European-American families: (a) within previously identified linkage region on chromosome 2, two significant GLI2-TFCP2L1 associations with weight, and (b) one chromosome 11 variant near CADM1-LINC00900 with pleiotropic blood pressure effects. Conclusions This multiethnic family study found genetic heterogeneity and coincident associations (with one case of pleiotropy), highlighting the importance of including diverse populations in genetic research and illustrating the complex genetic architecture underlying MetS.

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