scholarly journals Latent subtypes of manic and/or irritable episode symptoms in two population-based cohorts

2022 ◽  
pp. 1-10
Author(s):  
Ryan Arathimos ◽  
Chiara Fabbri ◽  
Evangelos Vassos ◽  
Katrina A. S. Davis ◽  
Oliver Pain ◽  
...  
Keyword(s):  
Mood Disorders ◽  
Functional Outcomes ◽  
Latent Class ◽  
Classification Systems ◽  
Polygenic Risk Score ◽  
Latent Classes ◽  
Uk Biobank ◽  
Polygenic Risk ◽  
Diagnostic Threshold ◽  
Irritable Mood

Background Mood disorders are characterised by pronounced symptom heterogeneity, which presents a substantial challenge both to clinical practice and research. Identification of subgroups of individuals with homogeneous symptom profiles that cut across current diagnostic categories could provide insights in to the transdiagnostic relevance of individual symptoms, which current categorical diagnostic systems cannot impart. Aims To identify groups of people with homogeneous clinical characteristics, using symptoms of manic and/or irritable mood, and explore differences between groups in diagnoses, functional outcomes and genetic liability. Method We used latent class analysis on eight binary self-reported symptoms of manic and irritable mood in the UK Biobank and PROTECT studies, to investigate how individuals formed latent subgroups. We tested associations between the latent classes and diagnoses of psychiatric disorders, sociodemographic characteristics and polygenic risk scores. Results Five latent classes were derived in UK Biobank (N = 42 183) and were replicated in the independent PROTECT cohort (N = 4445), including ‘minimally affected’, ‘inactive restless’, active restless’, ‘focused creative’ and ‘extensively affected’ individuals. These classes differed in disorder risk, polygenic risk score and functional outcomes. One class that experienced disruptive episodes of mostly irritable mood largely comprised cases of depression/anxiety, and a class of individuals with increased confidence/creativity reported comparatively lower disruptiveness and functional impairment. Conclusions Findings suggest that data-driven investigations of psychopathological symptoms that include sub-diagnostic threshold conditions can complement research of clinical diagnoses. Improved classification systems of psychopathology could investigate a weighted approach to symptoms, toward a more dimensional classification of mood disorders.

scholarly journals Latent subtypes of manic or irritable episode symptoms in two population-based cohorts

2021 ◽  
Author(s):  
Ryan Arathimos ◽  
Chiara Fabbri ◽  
Evangelos Vassos ◽  
Katrina A S Davis ◽  
Oliver Pain ◽  
...  
Keyword(s):  
Mood Disorders ◽  
Latent Class ◽  
Epidemiological Studies ◽  
Data Driven ◽  
Risk Scores ◽  
Latent Classes ◽  
Uk Biobank ◽  
Data Driven Approach ◽  
Latent Subgroups ◽  
Irritable Mood

Background Episodic changes in mood characterise disorders such as bipolar disorder, which includes distinct periods of manic excitability or irritability, along with additional symptoms experienced during these periods. Common clinical understanding informs diagnostic criteria and epidemiological studies reflect clinical thresholds. Aims To use a data-driven approach to defining groupings of symptoms experienced during periods of manic or irritable mood, which could inform understanding of mood disorders and guide case classification by identifying subgroups with homogeneous clinical/functional outcomes. Methods We used latent class analysis (LCA) to conduct an exploration of the latent structure in symptom responses in the UK Biobank and PROTECT studies, by investigating how symptoms, experienced during periods of manic or irritable mood, formed latent subgroups. We tested associations of latent subgroups with sociodemographic characteristics, diagnoses of psychiatric disorders and polygenic risk scores (PRS). Results Five latent classes were identified that captured patterns of symptoms experienced during periods of manic or irritable mood (N=42,183) in UK Biobank. We identified one class that experienced disruptive episodes of mostly irritable mood that was largely comprised of cases of depression/anxiety, and a class of individuals with increased confidence/creativity that reported lower disruptiveness and lower functional impairment. The five latent classes were replicated in an independent cohort, the PROTECT study (N=4,445), with similar distinctions between classes. Conclusion Our data-driven approach to grouping individuals identified distinct latent classes. A dimensional classification of mood disorders informed by our findings will be able to better assess or subtype these disorders in future studies.

Symptom dimensions of major depression in a large community-based cohort

2021 ◽  
pp. 1-8
Author(s):  
Michael Wainberg ◽  
Peter Zhukovsky ◽  
Sean L. Hill ◽  
Daniel Felsky ◽  
Aristotle Voineskos ◽  
...  
Keyword(s):  
Primary Care ◽  
Major Depression ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Psychiatric Diagnoses ◽  
Uk Biobank ◽  
Community Based ◽  
Symptom Dimensions ◽  
Polygenic Risk ◽  
Large Community

Abstract Background Our understanding of major depression is complicated by substantial heterogeneity in disease presentation, which can be disentangled by data-driven analyses of depressive symptom dimensions. We aimed to determine the clinical portrait of such symptom dimensions among individuals in the community. Methods This cross-sectional study consisted of 25 261 self-reported White UK Biobank participants with major depression. Nine questions from the UK Biobank Mental Health Questionnaire encompassing depressive symptoms were decomposed into underlying factors or ‘symptom dimensions’ via factor analysis, which were then tested for association with psychiatric diagnoses and polygenic risk scores for major depressive disorder (MDD), bipolar disorder and schizophrenia. Replication was performed among 655 self-reported non-White participants, across sexes, and among 7190 individuals with an ICD-10 code for MDD from linked inpatient or primary care records. Results Four broad symptom dimensions were identified, encompassing negative cognition, functional impairment, insomnia and atypical symptoms. These dimensions replicated across ancestries, sexes and individuals with inpatient or primary care MDD diagnoses, and were also consistent among 43 090 self-reported White participants with undiagnosed self-reported depression. Every dimension was associated with increased risk of nearly every psychiatric diagnosis and polygenic risk score. However, while certain psychiatric diagnoses were disproportionately associated with specific symptom dimensions, the three polygenic risk scores did not show the same specificity of associations. Conclusions An analysis of questionnaire data from a large community-based cohort reveals four replicable symptom dimensions of depression with distinct clinical, but not genetic, correlates.

1134-P: Polygenic Risk Score of Type 2 Diabetes as a Predictive Factor for Macrovascular Complications: A Prospective Population-Based UK Biobank Study

Diabetes ◽  
2021 ◽  
Vol 70 (Supplement 1) ◽  
pp. 1134-P
Author(s):  
SANGHYUK JUNG ◽  
DOKYOON KIM ◽  
MANU SHIVAKUMAR ◽  
HONG-HEE WON ◽  
JAE-SEUNG YUN
Keyword(s):  
Type 2 Diabetes ◽  
Risk Score ◽  
Predictive Factor ◽  
Population Based ◽  
Macrovascular Complications ◽  
Polygenic Risk Score ◽  
Uk Biobank ◽  
Polygenic Risk

Polygenic Risk Scores for Kidney Function and Their Associations with Circulating Proteome, and Incident Kidney Diseases

2021 ◽  
pp. ASN.2020111599
Author(s):  
Zhi Yu ◽  
Jin Jin ◽  
Adrienne Tin ◽  
Anna Köttgen ◽  
Bing Yu ◽  
...  
Keyword(s):  
Kidney Function ◽  
Kidney Diseases ◽  
Association Studies ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Plasma Proteome ◽  
Uk Biobank ◽  
Polygenic Risk ◽  
Genome Wide ◽  
A Genome

Background: Genome-wide association studies (GWAS) have revealed numerous loci for kidney function (estimated glomerular filtration rate, eGFR). The relationship of polygenic predictors of eGFR, risk of incident adverse kidney outcomes, and the plasma proteome is not known. Methods: We developed a genome-wide polygenic risk score (PRS) for eGFR by applying the LDpred algorithm to summary statistics generated from a multiethnic meta-analysis of CKDGen Consortium GWAS (N=765,348) and UK Biobank GWAS (90% of the cohort; N=451,508), followed by best parameter selection using the remaining 10% of UK Biobank (N=45,158). We then tested the association of the PRS in the Atherosclerosis Risk in Communities (ARIC) study (N=8,866) with incident chronic kidney disease, kidney failure, and acute kidney injury. We also examined associations between the PRS and 4,877 plasma proteins measured at at middle age and older adulthood and evaluated mediation of PRS associations by eGFR. Results: The developed PRS showed significant associations with all outcomes with hazard ratios (95% CI) per 1 SD lower PRS ranged from 1.06 (1.01, 1.11) to 1.33 (1.28, 1.37). The PRS was significantly associated with 132 proteins at both time points. The strongest associations were with cystatin-C, collagen alpha-1(XV) chain, and desmocollin-2. Most proteins were higher at lower kidney function, except for 5 proteins including testican-2. Most correlations of the genetic PRS with proteins were mediated by eGFR. Conclusions: A PRS for eGFR is now sufficiently strong to capture risk for a spectrum of incident kidney diseases and broadly influences the plasma proteome, primarily mediated by eGFR.

scholarly journals Photoreceptor layer thinning is an early biomarker for age-related macular degeneration development: Epidemiological and genetic evidence from UK Biobank optical coherence tomography data

2021 ◽  
Author(s):  
Seyedeh Maryam Zekavat ◽  
Sayuri Sekimitsu ◽  
Yixuan Ye ◽  
Hongyu Zhao ◽  
Tobias Elze ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Macular Degeneration ◽  
Early Stage ◽  
Age Related Macular Degeneration ◽  
Retinal Layer ◽  
Polygenic Risk Score ◽  
Uk Biobank ◽  
Polygenic Risk ◽  
Age Related ◽  
Clinical Biomarker

AbstractIntroductionAge-related macular degeneration (AMD) is a blinding condition for which there is currently no early-stage clinical biomarker. AMD is characterized by thinning of the outer retina and drusen formation leading to thickening of the Bruch’s membrane and RPE complex, but the timing between these two events, as well as the role of genetic variants in these processes, are unclear. Here, we jointly analyzed genomic, electronic health record, and optical coherence tomography (OCT) data across 44,823 individuals from the UK Biobank to characterize the epidemiological and genetic associations between retinal layer thicknesses and AMD.MethodsThe Topcon Advanced Boundary Segmentation algorithm was used for automated retinal layer segmentation. We associated 9 retinal layer thicknesses with prevalent AMD (present at enrollment) in a logistic regression model, and with incident AMD (diagnosed after enrollment) in a Cox proportional hazards model. Next, we tested the association of AMD-associated genetic alleles, individually and as a polygenic risk score (PRS), with retinal layer thicknesses. All analyses were adjusted for age, age2, sex, smoking status, and principal components of ancestry.ResultsPhotoreceptor segment (PS) thinning was observed throughout the lifespan of individuals analyzed and accelerated at age 45, while retinal pigment epithelium and Bruch’s membrane complex (RPE+BM) thickening started after age 57. Each standard deviation (SD) of PS thinning and RPE+BM thickening were associated with prevalent AMD (PS: OR 1.37, 95% CI 1.25-1.49, P=2.5×10−12; RPE+BM: OR=1.34, 95% CI 1.27-1.41, P=8.4×10−28) and incident AMD (PS: HR 1.35, 95% CI 1.23-1.47, P=3.7×10−11; RPE+BM: HR 1.14, 95% CI 1.06-1.22, P=0.00024). An AMD polygenic risk score (PRS) was associated with PS thinning (Beta -0.21 SD per 2-fold genetically increased risk of AMD, 95% CI -0.23 to -0.19, P=2.8×10−74), and its association with RPE+BM was U-shaped (thinning with AMD PRS<92nd percentile and thickening with AMD PRS>92nd percentile suggestive of drusen formation). The loci with strongest support were AMD risk-raising variants CFH:rs570618-T, CFH:10922109-C, and ARMS2/HTRA1:rs3750846-C on PS thinning, and SYN3/TIMP3:rs5754227-T on RPE+BM thickening.ConclusionsEpidemiologically, PS thinning precedes RPE+BM thickening by decades, and is the retinal layer most strongly predictive of future AMD risk. Genetically, AMD risk variants are associated with decreased PS thickness. Overall, these findings support PS thinning as an early-stage clinical biomarker for future AMD development.

scholarly journals The undiagnosed disease burden associated with alpha-1 antitrypsin deficiency genotypes

2020 ◽  
Vol 56 (6) ◽  
pp. 2001441 ◽  
Author(s):  
Tomoko Nakanishi ◽  
Vincenzo Forgetta ◽  
Tomohiro Handa ◽  
Toyohiro Hirai ◽  
Vincent Mooser ◽  
...  
Keyword(s):  
Risk Score ◽  
Disease Burden ◽  
Forced Expiratory Volume ◽  
European Ancestry ◽  
Polygenic Risk Score ◽  
Uk Biobank ◽  
Polygenic Risk ◽  
Antitrypsin Deficiency ◽  
Alpha 1 Antitrypsin Deficiency ◽  
Alpha 1 Antitrypsin

Alpha-1 antitrypsin deficiency (AATD), mainly due to the PI*ZZ genotype in SERPINA1, is one of the most common inherited diseases. Since it is associated with a high disease burden and partially prevented by smoking cessation, identification of PI*ZZ individuals through genotyping could improve health outcomes.We examined the frequency of the PI*ZZ genotype in individuals with and without diagnosed AATD from UK Biobank, and assessed the associations of the genotypes with clinical outcomes and mortality. A phenome-wide association study (PheWAS) was conducted to reveal disease associations with genotypes. A polygenic risk score (PRS) for forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC) ratio was used to evaluate variable penetrance of PI*ZZ.Among 458 164 European-ancestry participants in UK Biobank, 140 had the PI*ZZ genotype and only nine (6.4%, 95% CI 3.4–11.7%) of them were diagnosed with AATD. Those with PI*ZZ had a substantially higher odds of COPD (OR 8.8, 95% CI 5.8–13.3), asthma (OR 2.0, 95% CI 1.4–3.0), bronchiectasis (OR 7.3, 95%CI 3.2–16.8), pneumonia (OR 2.7, 95% CI 1.5–4.9) and cirrhosis (OR 7.8, 95% CI 2.5–24.6) diagnoses and a higher hazard of mortality (2.4, 95% CI 1.2–4.6), compared to PI*MM (wildtype) (n=398 424). These associations were stronger among smokers. PheWAS demonstrated associations with increased odds of empyema, pneumothorax, cachexia, polycythaemia, aneurysm and pancreatitis. Polygenic risk score and PI*ZZ were independently associated with FEV1/FVC <0.7 (OR 1.4 per 1-sd change, 95% CI 1.4–1.5 and OR 4.5, 95% CI 3.0–6.9, respectively).The important underdiagnosis of AATD, whose outcomes are partially preventable through smoking cession, could be improved through genotype-guided diagnosis.

scholarly journals Phenome-wide Mendelian-randomization study of genetically determined vitamin D on multiple health outcomes using the UK Biobank study

2019 ◽  
Vol 48 (5) ◽  
pp. 1425-1434 ◽  
Author(s):  
Xiangrui Meng ◽  
Xue Li ◽  
Maria N Timofeeva ◽  
Yazhou He ◽  
Athina Spiliopoulou ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Vitamin D ◽  
Health Outcomes ◽  
Mendelian Randomization ◽  
Causal Effects ◽  
Polygenic Risk Score ◽  
Uk Biobank ◽  
Polygenic Risk ◽  
Disease Outcomes ◽  
Multiple Health

Abstract Background Vitamin D deficiency is highly prevalent across the globe. Existing studies suggest that a low vitamin D level is associated with more than 130 outcomes. Exploring the causal role of vitamin D in health outcomes could support or question vitamin D supplementation. Methods We carried out a systematic literature review of previous Mendelian-randomization studies on vitamin D. We then implemented a Mendelian Randomization–Phenome Wide Association Study (MR-PheWAS) analysis on data from 339 256 individuals of White British origin from UK Biobank. We first ran a PheWAS analysis to test the associations between a 25(OH)D polygenic risk score and 920 disease outcomes, and then nine phenotypes (i.e. systolic blood pressure, diastolic blood pressure, risk of hypertension, T2D, ischaemic heart disease, body mass index, depression, non-vertebral fracture and all-cause mortality) that met the pre-defined inclusion criteria for further analysis were examined by multiple MR analytical approaches to explore causality. Results The PheWAS analysis did not identify any health outcome associated with the 25(OH)D polygenic risk score. Although a selection of nine outcomes were reported in previous Mendelian-randomization studies or umbrella reviews to be associated with vitamin D, our MR analysis, with substantial study power (>80% power to detect an association with an odds ratio >1.2 for per standard deviation increase of log-transformed 25[OH]D), was unable to support an interpretation of causal association. Conclusions We investigated the putative causal effects of vitamin D on multiple health outcomes in a White population. We did not support a causal effect on any of the disease outcomes tested. However, we cannot exclude small causal effects or effects on outcomes that we did not have enough power to explore due to the small number of cases.

scholarly journals Self-reported hearing loss questions provide a good measure for genetic studies: a polygenic risk score analysis from UK Biobank

2020 ◽  
Vol 28 (8) ◽  
pp. 1056-1065
Author(s):  
Stacey S. Cherny ◽  
Gregory Livshits ◽  
Helena R. R. Wells ◽  
Maxim B. Freidin ◽  
Ida Malkin ◽  
...  
Keyword(s):  
Hearing Loss ◽  
Risk Score ◽  
Good Measure ◽  
Polygenic Risk Score ◽  
Uk Biobank ◽  
Genetic Studies ◽  
Polygenic Risk ◽  
Score Analysis

scholarly journals Diet quality indices, genetic risk and risk of cardiovascular disease and mortality: a longitudinal analysis of 77 004 UK Biobank participants

BMJ Open ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. e045362
Author(s):  
Katherine M Livingstone ◽  
Gavin Abbott ◽  
Steven J Bowe ◽  
Joey Ward ◽  
Catherine Milte ◽  
...  
Keyword(s):  
Risk Score ◽  
Diet Quality ◽  
Genetic Risk ◽  
Lower Risk ◽  
Polygenic Risk Score ◽  
Uk Biobank ◽  
Quality Indices ◽  
Polygenic Risk ◽  
All Cause Mortality ◽  
Cvd Mortality

ObjectivesTo examine associations of three diet quality indices and a polygenic risk score with incidence of all-cause mortality, cardiovascular disease (CVD) mortality, myocardial infarction (MI) and stroke.DesignProspective cohort study.SettingUK Biobank, UK.Participants77 004 men and women (40–70 years) recruited between 2006 and 2010.Main outcome measuresA polygenic risk score was created from 300 single nucleotide polymorphisms associated with CVD. Cox proportional HRs were used to estimate independent effects of diet quality and genetic risk on all-cause mortality, CVD mortality, MI and stroke risk. Dietary intake (Oxford WebQ) was used to calculate Recommended Food Score (RFS), Healthy Diet Indicator (HDI) and Mediterranean Diet Score (MDS).ResultsNew all-cause (n=2409) and CVD (n=364) deaths and MI (n=1141) and stroke (n=748) events were identified during mean follow-ups of 7.9 and 7.8 years, respectively. The adjusted HR associated with one-point higher RFS for all-cause mortality was 0.96 (95% CI: 0.94 to 0.98), CVD mortality was 0.94 (95% CI: 0.90 to 0.98), MI was 0.97 (95% CI: 0.95 to 1.00) and stroke was 0.94 (95% CI: 0.91 to 0.98). The adjusted HR for all-cause mortality associated with one-point higher HDI and MDS was 0.97 (95% CI: 0.93 to 0.99) and 0.95 (95% CI: 0.91 to 0.98), respectively. The adjusted HR associated with one-point higher MDS for stroke was 0.93 (95% CI: 0.87 to 1.00). There was little evidence of associations between HDI and risk of CVD mortality, MI or stroke. There was evidence of an interaction between diet quality and genetic risk score for MI.ConclusionHigher diet quality predicted lower risk of all-cause mortality, independent of genetic risk. Higher RFS was also associated with lower risk of CVD mortality and MI. These findings demonstrate the benefit of following a healthy diet, regardless of genetic risk.

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