Whole Genome Sequencing in Psychiatric Disorders: the WGSPD Consortium

As technology advances, whole genome sequencing (WGS) is likely to supersede other genotyping technologies. The rate of this change depends on its relative cost and utility. Variants identified uniquely through WGS may reveal novel biological pathways underlying complex disorders and provide high-resolution insight into when, where, and in which cell type these pathways are affected. Alternatively, cheaper and less computationally intensive approaches may yield equivalent insights. Understanding the role of rare variants in the noncoding gene-regulating genome, through pilot WGS projects, will be critical to determine which of these two extremes best represents reality. With large cohorts, well-defined risk loci, and a compelling need to understand the underlying biology, psychiatric disorders have a role to play in this preliminary WGS assessment. The WGSPD consortium will integrate data for 18,000 individuals with psychiatric disorders, beginning with autism spectrum disorder, schizophrenia, bipolar disorder, and major depressive disorder, along with over 150,000 controls

Data for Genetic Analysis Workshop 18: human whole genome sequence, blood pressure, and simulated phenotypes in extended pedigrees

Genetic Analysis Workshop 18 (GAW18) focused on identification of genes and functional variants that influence complex phenotypes in human sequence data. Data for the workshop were donated by the T2D-GENES Consortium and included whole genome sequences for odd-numbered autosomes in 464 key individuals selected from 20 Mexican American families, a dense set of single-nucleotide polymorphisms in 959 individuals in these families, and longitudinal data on systolic and diastolic blood pressure measured at 1-4 examinations over a period of 20 years. Simulated phenotypes were generated based on the real sequence data and pedigree structures. In the design of the simulation model, gene expression measures from the San Antonio Family Heart Study (not distributed as part of the GAW18 data) were used to identify genes whose mRNA levels were correlated with blood pressure. Observed variants within these genes were designated as functional in the GAW18 simulation if they were nonsynonymous and predicted to have deleterious effects on protein function or if they were noncoding and associated with mRNA levels. Two simulated longitudinal phenotypes were modeled to have the same trait distributions as the real systolic and diastolic blood pressure data, with effects of age, sex, and medication use, including a genotype-medication interaction. For each phenotype, more than 1000 sequence variants in more than 200 genes present on the odd-numbered autosomes individually explained less than 0.01-2.78% of phenotypic variance. Cumulatively, variants in the most influential gene explained 7.79% of trait variance. An additional simulated phenotype, Q1, was designed to be correlated among family members but to not be associated with any sequence variants. Two hundred replicates of the phenotypes were simulated, with each including data for 849 individuals

Characteristics of long-COVID among older adults: a cross-sectional study

Objectives: To describe long-COVID symptoms among older adults and to assess the risk factors for two common long-COVID symptoms: fatigue and dyspnea. Methods: This is a multicenter, prospective cohort study conducted in Israel, Switzerland, Spain, and Italy. Individuals were included at least 30 days after their COVID-19 diagnosis. We compared long-COVID symptoms between elderly (aged >65 years) and younger individuals (aged 18-65 years) and conducted univariate and multivariable analyses for the predictors of long-COVID fatigue and dyspnea. Results: A total of 2333 individuals were evaluated at an average of 5 months (146 days [95% confidence interval 142-150]) after COVID-19 onset. The mean age was 51 years, and 20.5% were aged >65 years. Older adults were more likely to be symptomatic, with the most common symptoms being fatigue (38%) and dyspnea (30%); they were more likely to complain of cough and arthralgia and have abnormal chest imaging and pulmonary function tests. Independent risk factors for long-COVID fatigue and dyspnea included female gender, obesity, and closer proximity to COVID-19 diagnosis; older age was not an independent predictor. Conclusion: Older individuals with long-COVID have different persisting symptoms, with more pronounced pulmonary impairment. Women and individuals with obesity are at risk. Further research is warranted to investigate the natural history of long-COVID among the elderly population and to assess possible interventions aimed at promoting rehabilitation and well-being

Characteristics of long COVID among older adults: a cross-sectional study

To describe long-COVID symptoms among older adults, and to assess risk factors for two common long-COVID symptoms: fatigue and dyspnea

Genome-Wide Association Study of Plasma Polyunsaturated Fatty Acids in the InCHIANTI Study

Polyunsaturated fatty acids (PUFA) have a role in many physiological processes, including energy production, modulation of inflammation, and maintenance of cell membrane integrity. High plasma PUFA concentrations have been shown to have beneficial effects on cardiovascular disease and mortality. To identify genetic contributors of plasma PUFA concentrations, we conducted a genome-wide association study of plasma levels of six omega-3 and omega-6 fatty acids in 1,075 participants in the InCHIANTI study on aging. The strongest evidence for association was observed in a region of chromosome 11 that encodes three fatty acid desaturases (FADS1, FADS2, FADS3). The SNP with the most significant association was rs174537 near FADS1 in the analysis of arachidonic acid (AA; p = 5.95×10−46). Minor allele homozygotes had lower AA compared to the major allele homozygotes and rs174537 accounted for 18.6% of the additive variance in AA concentrations. This SNP was also associated with levels of eicosadienoic acid (EDA; p = 6.78×10−9) and eicosapentanoic acid (EPA; p = 1.07×10−14). Participants carrying the allele associated with higher AA, EDA, and EPA also had higher low-density lipoprotein (LDL-C) and total cholesterol levels. Outside the FADS gene cluster, the strongest region of association mapped to chromosome 6 in the region encoding an elongase of very long fatty acids 2 (ELOVL2). In this region, association was observed with EPA (rs953413; p = 1.1×10−6). The effects of rs174537 were confirmed in an independent sample of 1,076 subjects participating in the GOLDN study. The ELOVL2 SNP was associated with docosapentanoic and DHA but not with EPA in GOLDN. These findings show that polymorphisms of genes encoding enzymes in the metabolism of PUFA contribute to plasma concentrations of fatty acids

An investigation of the effects of lipid-lowering medications: genome-wide linkage analysis of lipids in the HyperGEN study

BACKGROUND: Use of anti-hyperlipidemic medications compromises genetic analysis because of altered lipid profiles. We propose an empirical method to adjust lipid levels for medication effects so that the adjusted lipid values substitute the unmedicated lipid values in the genetic analysis. RESULTS: Published clinical trials were reviewed for HMG-CoA reductase inhibitors and fibric acid derivatives as mono-drug therapy. HMG-CoA reductase inhibitors showed similar effects in African Americans (AA) and non-African Americans (non-AA) for lowering total cholesterol (TC, -50.7 mg/dl), LDL cholesterol (LDL-C, -48.1 mg/dl), and triglycerides (TG, -19.7 mg/dl). Their effect on increasing HDL cholesterol (HDL-C) in AA (+0.4 mg/dl) was lower than in Non-AA (+2.3 mg/dl). The effects of fibric acid derivatives were estimated as -46.1 mg/dl for TC, -40.1 mg/dl for LDL-C, and +5.9 mg/dl for HDL-C in non-AA. The corresponding effects in AA were less extreme (-20.1 mg/dl, -11.4 mg/dl, and +3.1 mg/dl). Similar effect for TG (59.0 mg/dl) was shown in AA and non-AA. The above estimated effects were applied to a multipoint variance components linkage analysis on the lipid levels in 2,403 Whites and 2,214 AA in the HyperGEN study. The familial effects did vary depending on whether the lipids were adjusted for medication use. For example, the heritabilities increased after medication adjustment for TC and LDL-C, but did not change significantly for HDL-C and TG. CONCLUSION: Ethnicity-specific medication adjustments using our empirical method can be employed in epidemiological and genetic analysis of lipids.National Heart, Lung, and Blood Institute (HL554471, HL54472, HL54473, HL54495, HL54496, HL54497, HL54509, HL54515