KIF15 missense variant is associated with the early onset of idiopathic pulmonary fibrosis.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) has an unknown aetiology and limited treatment options. A recent meta-analysis identified three novel causal variants in the TERT, SPDL1, and KIF15 genes. This observational study aimed to investigate whether the aforementioned variants cause clinical phenotypes in a well-characterised IPF cohort. METHODS: The study consisted of 138 patients with IPF who were diagnosed and treated at the Helsinki University Hospital and genotyped in the FinnGen FinnIPF study. Data on > 25 clinical parameters were collected by two pulmonologists who were blinded to the genetic data for patients with TERT loss of function and missense variants, SPDL1 and KIF15 missense variants, and a MUC5B variant commonly present in patients with IPF, or no variants were separately analysed. RESULTS: The KIF15 missense variant is associated with the early onset of the disease, leading to progression to early-age transplantation or death. In patients with the KIF15 variant, the median age at diagnosis was 54.0 years (36.5-69.5 years) compared with 72.0 years (65.8-75.3 years) in the other patients (P = 0.023). The proportion of KIF15 variant carriers was 9- or 3.6-fold higher in patients aged < 55 or 65 years, respectively. The variants for TERT and MUC5B had similar effects on the patient's clinical course, as previously described. No distinct phenotypes were observed in patients with the SPDL1 variant. CONCLUSIONS: Our study indicated the potential of KIF15 to be used in the genetic diagnostics of IPF. Further studies are needed to elucidate the biological mechanisms of KIF15 in IPF.

Polygenic burden has broader impact on health, cognition, and socioeconomic outcomes than most rare and high-risk copy number variants.

Copy number variants (CNVs) are associated with syndromic and severe neurological and psychiatric disorders (SNPDs), such as intellectual disability, epilepsy, schizophrenia, and bipolar disorder. Although considered high-impact, CNVs are also observed in the general population. This presents a diagnostic challenge in evaluating their clinical significance. To estimate the phenotypic differences between CNV carriers and non-carriers regarding general health and well-being, we compared the impact of SNPD-associated CNVs on health, cognition, and socioeconomic phenotypes to the impact of three genome-wide polygenic risk score (PRS) in two Finnish cohorts (FINRISK, n = 23,053 and NFBC1966, n = 4895). The focus was on CNV carriers and PRS extremes who do not have an SNPD diagnosis. We identified high-risk CNVs (DECIPHER CNVs, risk gene deletions, or large [>1 Mb] CNVs) in 744 study participants (2.66%), 36 (4.8%) of whom had a diagnosed SNPD. In the remaining 708 unaffected carriers, we observed lower educational attainment (EA; OR = 0.77 [95% CI 0.66-0.89]) and lower household income (OR = 0.77 [0.66-0.89]). Income-associated CNVs also lowered household income (OR = 0.50 [0.38-0.66]), and CNVs with medical consequences lowered subjective health (OR = 0.48 [0.32-0.72]). The impact of PRSs was broader. At the lowest extreme of PRS for EA, we observed lower EA (OR = 0.31 [0.26-0.37]), lower-income (OR = 0.66 [0.57-0.77]), lower subjective health (OR = 0.72 [0.61-0.83]), and increased mortality (Cox's HR = 1.55 [1.21-1.98]). PRS for intelligence had a similar impact, whereas PRS for schizophrenia did not affect these traits. We conclude that the majority of working-age individuals carrying high-risk CNVs without SNPD diagnosis have a modest impact on morbidity and mortality, as well as the limited impact on income and educational attainment, compared to individuals at the extreme end of common genetic variation. Our findings highlight that the contribution of traditional high-risk variants such as CNVs should be analyzed in a broader genetic context, rather than evaluated in isolation.

Polygenic liability for antipsychotic dosage and polypharmacy - a real-world registry and biobank study.

Genomic prediction of antipsychotic dose and polypharmacy has been difficult, mainly due to limited access to large cohorts with genetic and drug prescription data. In this proof of principle study, we investigated if genetic liability for schizophrenia is associated with high dose requirements of antipsychotics and antipsychotic polypharmacy, using real-world registry and biobank data from five independent Nordic cohorts of a total of N = 21,572 individuals with psychotic disorders (schizophrenia, bipolar disorder, and other psychosis). Within regression models, a polygenic risk score (PRS) for schizophrenia was studied in relation to standardized antipsychotic dose as well as antipsychotic polypharmacy, defined based on longitudinal prescription registry data as well as health records and self-reported data. Meta-analyses across the five cohorts showed that PRS for schizophrenia was significantly positively associated with prescribed (standardized) antipsychotic dose (beta(SE) = 0.0435(0.009), p = 0.0006) and antipsychotic polypharmacy defined as taking ≥2 antipsychotics (OR = 1.10, CI = 1.05-1.21, p = 0.0073). The direction of effect was similar in all five independent cohorts. These findings indicate that genotypes may aid clinically relevant decisions on individual patients´ antipsychotic treatment. Further, the findings illustrate how real-world data have the potential to generate results needed for future precision medicine approaches in psychiatry.

How Communicating Polygenic and Clinical Risk for Atherosclerotic Cardiovascular Disease Impacts Health Behavior: an Observational Follow-up Study.

BACKGROUND: Prediction tools that combine polygenic risk scores with clinical factors provide a new opportunity for improved prediction and prevention of atherosclerotic cardiovascular disease, but the clinical utility of polygenic risk score has remained unclear. METHODS: We collected a prospective cohort of 7342 individuals (64% women, mean age 56 years) and estimated their 10-year risk for atherosclerotic cardiovascular disease both by a traditional risk score and a composite score combining the effect of a polygenic risk score and clinical risk factors. We then tested how returning the personal risk information with an interactive web-tool impacted on the participants' health behavior. RESULTS: When reassessed after 1.5 years by a clinical visit and questionnaires, 20.8% of individuals at high (>10%) 10-year atherosclerotic cardiovascular disease risk had seen a doctor, 12.4% reported weight loss, 14.2% of smokers had quit smoking, and 15.4% had signed up for health coaching online. Altogether, 42.6% of persons at high risk had made one or more health behavioral changes versus 33.5% of persons at low/average risk such that higher baseline risk predicted a favorable change (OR [CI], 1.53 [1.37-1.72] for persons at high risk versus the rest, P<0.001), with both high clinical (P<0.001) and genomic risk (OR [CI], 1.10 [1.03-1.17], P=0.003) contributing independently. CONCLUSIONS: Web-based communication of personal atherosclerotic cardiovascular disease risk-data including polygenic risk to middle-aged persons motivates positive changes in health behavior and the propensity to seek care. It supports integration of genomic information into clinical risk calculators as a feasible approach to enhance disease prevention.

Leveraging global multi-ancestry meta-analysis in the study of idiopathic pulmonary fibrosis genetics.

The research of rare and devastating orphan diseases, such as idiopathic pulmonary fibrosis (IPF) has been limited by the rarity of the disease itself. The prognosis is poor-the prevalence of IPF is only approximately four times the incidence, limiting the recruitment of patients to trials and studies of the underlying biology. Global biobanking efforts can dramatically alter the future of IPF research. We describe a large-scale meta-analysis of IPF, with 8,492 patients and 1,355,819 population controls from 13 biobanks around the globe. Finally, we combine this meta-analysis with the largest available meta-analysis of IPF, reaching 11,160 patients and 1,364,410 population controls. We identify seven novel genome-wide significant loci, only one of which would have been identified if the analysis had been limited to European ancestry individuals. We observe notable pleiotropy across IPF susceptibility and severe COVID-19 infection and note an unexplained sex-heterogeneity effect at the strongest IPF locus MUC5B.

Global Biobank Meta-analysis Initiative: Powering genetic discovery across human disease.

Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)-a collaborative network of 23 biobanks from 4 continents representing more than 2.2 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWASs generated using harmonized genotypes and phenotypes from member biobanks for 14 exemplar diseases and endpoints. This strategy validates that GWASs conducted in diverse biobanks can be integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics. This collaborative effort improves GWAS power for diseases, benefits understudied diseases, and improves risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of human diseases and traits.

An expanded analysis framework for multivariate GWAS connects inflammatory biomarkers to functional variants and disease.

Multivariate methods are known to increase the statistical power to detect associations in the case of shared genetic basis between phenotypes. They have, however, lacked essential analytic tools to follow-up and understand the biology underlying these associations. We developed a novel computational workflow for multivariate GWAS follow-up analyses, including fine-mapping and identification of the subset of traits driving associations (driver traits). Many follow-up tools require univariate regression coefficients which are lacking from multivariate results. Our method overcomes this problem by using Canonical Correlation Analysis to turn each multivariate association into its optimal univariate Linear Combination Phenotype (LCP). This enables an LCP-GWAS, which in turn generates the statistics required for follow-up analyses. We implemented our method on 12 highly correlated inflammatory biomarkers in a Finnish population-based study. Altogether, we identified 11 associations, four of which (F5, ABO, C1orf140 and PDGFRB) were not detected by biomarker-specific analyses. Fine-mapping identified 19 signals within the 11 loci and driver trait analysis determined the traits contributing to the associations. A phenome-wide association study on the 19 representative variants from the signals in 176,899 individuals from the FinnGen study revealed 53 disease associations (p < 1 × 10-4). Several reported pQTLs in the 11 loci provided orthogonal evidence for the biologically relevant functions of the representative variants. Our novel multivariate analysis workflow provides a powerful addition to standard univariate GWAS analyses by enabling multivariate GWAS follow-up and thus promoting the advancement of powerful multivariate methods in genomics.

Discrimination hurts: The effect of discrimination on the development of chronic pain.

We examine the hypothesis that psychological distress due to perceived discrimination can result in chronic pain, where perceived discrimination is based on age, gender, race, ethnicity, disability, sexual orientation, height/weight, religion, and other characteristics. Using a sample of 1908 individuals from the two most recent waves (2004-2006 and 2013-2014) of panel data from the National Survey of Midlife Development in the United States, we apply instrumental variables regression where measures of daily and lifetime perceived discrimination are instruments whose effects on chronic pain are mediated by psychological distress. We find statistically significant dose-response relationships between daily perceived discrimination and psychological distress, between lifetime perceived discrimination and psychological distress, and between psychological distress and chronic pain. Based on our instrumental variables regression model, we estimate that 4.1 million people in the US in 2016, aged 40 and older, experience chronic pain that is caused by increased psychological distress, where psychological stress has increased due to perceived discrimination.

Correction: B-Cell Responses to Human Bocaviruses 1-4: New Insights from a Childhood Follow-Up Study.

[This corrects the article DOI: 10.1371/journal.pone.0139096.].

B-Cell Responses to Human Bocaviruses 1-4: New Insights from a Childhood Follow-Up Study.

Human bocaviruses (HBoVs) 1-4 are recently discovered, antigenically similar parvoviruses. We examined the hypothesis that the antigenic similarity of these viruses could give rise to clinically and diagnostically important immunological interactions. IgG and IgM EIAs as well as qPCR were used to study ~2000 sera collected from infancy to early adolescence at 3-6-month intervals from 109 children whose symptoms were recorded. We found that HBoV1-4-specific seroprevalences at age 6 years were 80%, 48%, 10%, and 0%, respectively. HBoV1 infections resulted in significantly weaker IgG responses among children who had pre-existing HBoV2 IgG, and vice versa. Furthermore, we documented a complete absence of virus type-specific immune responses in six viremic children who had pre-existing IgG for another bocavirus, indicating that not all HBoV infections can be diagnosed serologically. Our results strongly indicate that interactions between consecutive HBoV infections affect HBoV immunity via a phenomenon called "original antigenic sin", cross-protection, or both; however, without evident clinical consequences but with important ramifications for the serodiagnosis of HBoV infections. Serological data is likely to underestimate human exposure to these viruses.