scholarly journals Delineating genetic and familial risk for psychopathology in the ABCD study

2020 ◽  
Author(s):  
Clare E Palmer ◽  
Robert John Loughnan ◽  
Carolina Makowski ◽  
Wesley Thompson ◽  
Deanna Barch ◽  
...  
Keyword(s):  
Family History ◽  
Psychiatric Disorders ◽  
Genetic Risk ◽  
Familial Risk ◽  
Risk Scores ◽  
Typically Developing ◽  
Polygenic Risk ◽  
Hyperactivity Disorder ◽  
History Of ◽  
Risk Predictors

Psychiatric disorders place a huge burden on those affected and their families, as well as society. Nearly all psychiatric disorders have a heritable component and lifetime prevalence rates of several disorders are higher among first degree biological relatives of individuals with a diagnosis. Given that many psychiatric disorders have their onset in adolescence, estimating genetic risk during childhood may identify at-risk individuals for early intervention that can reduce this burden. Here we measured genetic risk for psychopathology using both polygenic risk scores (PRS) and family history in a large typically developing sample of 9-10 year old children from the Adolescent Brain and Cognitive Development (ABCD) StudySM and determined associations with a large battery of behavioural phenotypes. By including all genetic risk predictors in the same model, we were able to delineate unique behavioral associations across these measures. Polygenic risk for Attention Deficit Hyperactivity Disorder (ADHD) and depression (DEP) was associated with unique patterns of both externalizing and internalizing behaviors. Family history of conduct problems, depression and anxiety/stress additionally predicted unique behavioral variance across similar measures. These findings provide important insight into the potential predictive utility of PRS and family history in early adolescence and suggest that they may be signaling differential, additive information that could be useful for quantifying risk during development.

scholarly journals Dissecting clinical heterogeneity of bipolar disorder using multiple polygenic risk scores

2020 ◽  
Author(s):  
Brandon J. Coombes ◽  
Matej Markota ◽  
J. John Mann ◽  
Colin Colby ◽  
Eli Stahl ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Psychiatric Disorders ◽  
Suicide Attempts ◽  
Risk Scores ◽  
Rapid Cycling ◽  
Clinical Heterogeneity ◽  
Polygenic Risk ◽  
Clinical Observations ◽  
History Of ◽  
Dsm Iv

AbstractBipolar disorder (BD) has high clinical heterogeneity, frequent psychiatric comorbidities, and elevated suicide risk. To determine genetic differences between common clinical sub-phenotypes of BD, we performed a systematic PRS analysis using multiple polygenic risk scores (PRSs) from a range of psychiatric, personality, and lifestyle traits to dissect differences in BD sub-phenotypes in two BD cohorts: the Mayo Clinic BD Biobank (N = 968) and Genetic Association Information Network (N = 1001). Participants were assessed for history of psychosis, early-onset BD, rapid cycling (defined as four or more episodes in a year), and suicide attempts using questionnaires and the Structured Clinical Interview for DSM-IV. In a combined sample of 1969 bipolar cases (45.5% male), those with psychosis had higher PRS for SCZ (OR = 1.3 per S.D.; p = 3e-5) but lower PRSs for anhedonia (OR = 0.87; p = 0.003) and BMI (OR = 0.87; p = 0.003). Rapid cycling cases had higher PRS for ADHD (OR = 1.23; p = 7e-5) and MDD (OR = 1.23; p = 4e-5) and lower BD PRS (OR = 0.8; p = 0.004). Cases with a suicide attempt had higher PRS for MDD (OR = 1.26; p = 1e-6) and anhedonia (OR = 1.22; p = 2e-5) as well as lower PRS for educational attainment (OR = 0.87; p = 0.003). The observed novel PRS associations with sub-phenotypes align with clinical observations such as rapid cycling BD patients having a greater lifetime prevalence of ADHD. Our findings confirm that genetic heterogeneity underlies the clinical heterogeneity of BD and consideration of genetic contribution to psychopathologic components of psychiatric disorders may improve genetic prediction of complex psychiatric disorders.

scholarly journals Parkinson’s disease determinants, prediction and gene–environment interactions in the UK Biobank

2020 ◽  
Vol 91 (10) ◽  
pp. 1046-1054 ◽  
Author(s):  
Benjamin Meir Jacobs ◽  
Daniel Belete ◽  
Jonathan Bestwick ◽  
Cornelis Blauwendraat ◽  
Sara Bandres-Ciga ◽  
...  
Keyword(s):  
Risk Factors ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Family History ◽  
Genetic Risk ◽  
Positive Family History ◽  
Risk Scores ◽  
Uk Biobank ◽  
Gene Environment ◽  
History Of

ObjectiveTo systematically investigate the association of environmental risk factors and prodromal features with incident Parkinson’s disease (PD) diagnosis and the interaction of genetic risk with these factors. To evaluate whether existing risk prediction algorithms are improved by the inclusion of genetic risk scores.MethodsWe identified individuals with an incident diagnosis of PD (n=1276) and controls (n=500 406) in UK Biobank. We determined the association of risk factors with incident PD using adjusted logistic regression models. We constructed polygenic risk scores (PRSs) using external weights and selected the best PRS from a subset of the cohort (30%). The PRS was used in a separate testing set (70%) to examine gene–environment interactions and compare predictive models for PD.ResultsStrong evidence of association (false discovery rate <0.05) was found between PD and a positive family history of PD, a positive family history of dementia, non-smoking, low alcohol consumption, depression, daytime somnolence, epilepsy and earlier menarche. Individuals with the highest 10% of PRSs had increased risk of PD (OR 3.37, 95% CI 2.41 to 4.70) compared with the lowest risk decile. A higher PRS was associated with earlier age at PD diagnosis and inclusion of the PRS in the PREDICT-PD algorithm led to a modest improvement in model performance. We found evidence of an interaction between the PRS and diabetes.InterpretationHere, we used UK Biobank data to reproduce several well-known associations with PD, to demonstrate the validity of a PRS and to demonstrate a novel gene–environment interaction, whereby the effect of diabetes on PD risk appears to depend on background genetic risk for PD.

scholarly journals Incorporating family history of disease improves polygenic risk scores in diverse populations

2021 ◽  
Author(s):  
Margaux L.A. Hujoel ◽  
Po-Ru Loh ◽  
Benjamin M. Neale ◽  
Alkes L. Price
Keyword(s):  
Family History ◽  
Threshold Model ◽  
South Asians ◽  
Target Population ◽  
Risk Scores ◽  
Diverse Populations ◽  
Polygenic Risk ◽  
History Of Disease ◽  
History Of ◽  
Large Improvement

AbstractPolygenic risk scores derived from genotype data (PRS) and family history of disease (FH) both provide valuable information for predicting disease risk, enhancing prospects for clinical utility. PRS perform poorly when applied to diverse populations, but FH does not suffer this limitation. Here, we explore methods for combining both types of information (PRS-FH). We analyzed 10 complex diseases from the UK Biobank for which family history (parental and sibling history) was available for most target samples. PRS were trained using all British individuals (N=409K), and target samples consisted of unrelated non-British Europeans (N=42K), South Asians (N=7K), or Africans (N=7K). We evaluated PRS, FH, and PRS-FH using liability-scale R2, focusing on three well-powered diseases (type 2 diabetes, hypertension, depression) with R2 > 0.05 for PRS and/or FH in each target population. Averaging across these three diseases, PRS attained average prediction R2 of 5.8%, 4.0%, and 0.53% in non-British Europeans, South Asians, and Africans, confirming poor cross-population transferability. In contrast, PRS-FH attained average prediction R2 of 13%, 12%, and 10%, respectively, representing a large improvement in Europeans and an extremely large improvement in Africans; for each disease and each target population, the improvement was highly statistically significant. PRS-FH methods based on a logistic model and a liability threshold model performed similarly when covariates were not included in predictions (consistent with simulations), but the logistic model outperformed the liability threshold model when covariates were included. In conclusion, including family history greatly improves the accuracy of polygenic risk scores, particularly in diverse populations.

scholarly journals Polygenic Risk Score, Parental Socioeconomic Status, Family History of Psychiatric Disorders, and the Risk for Schizophrenia

2015 ◽  
Vol 72 (7) ◽  
pp. 635 ◽  
Author(s):  
Esben Agerbo ◽  
Patrick F. Sullivan ◽  
Bjarni J. Vilhjálmsson ◽  
Carsten B. Pedersen ◽  
Ole Mors ◽  
...  
Keyword(s):  
Socioeconomic Status ◽  
Family History ◽  
Psychiatric Disorders ◽  
Risk Score ◽  
Polygenic Risk Score ◽  
Polygenic Risk ◽  
History Of ◽  
Parental Socioeconomic Status

scholarly journals The association of polygenic risk for schizophrenia, bipolar disorder, and depression with neural connectivity in adolescents and young adults: examining developmental and sex differences

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
J. L. Meyers ◽  
D. B. Chorlian ◽  
T. B. Bigdeli ◽  
E. C. Johnson ◽  
F. Aliev ◽  
...  
Keyword(s):  
Young Adults ◽  
Sex Differences ◽  
Family History ◽  
Collaborative Study ◽  
Adolescents And Young Adults ◽  
Risk Scores ◽  
Eeg Coherence ◽  
Neural Connectivity ◽  
Polygenic Risk ◽  
History Of

AbstractNeurodevelopmental abnormalities in neural connectivity have been long implicated in the etiology of schizophrenia (SCZ); however, it remains unclear whether these neural connectivity patterns are associated with genetic risk for SCZ in unaffected individuals (i.e., an absence of clinical features of SCZ or a family history of SCZ). We examine whether polygenic risk scores (PRS) for SCZ are associated with functional neural connectivity in adolescents and young adults without SCZ, whether this association is moderated by sex and age, and if similar associations are observed for genetically related neuropsychiatric PRS. One-thousand four-hundred twenty-six offspring from 913 families, unaffected with SCZ, were drawn from the Collaborative Study of the Genetics of Alcoholism (COGA) prospective cohort (median age at first interview = 15.6 (12–26), 51.6% female, 98.1% European American, 41% with a family history of alcohol dependence). Participants were followed longitudinally with resting-state EEG connectivity (i.e., coherence) assessed every two years. Higher SCZ PRS were associated with elevated theta (3–7 Hz) and alpha (7–12 Hz) EEG coherence. Associations differed by sex and age; the most robust associations were observed between PRS and parietal-occipital, central-parietal, and frontal-parietal alpha coherence among males between ages 15–19 (B: 0.15–0.21, p < 10–4). Significant associations among EEG coherence and Bipolar and Depression PRS were observed, but differed from SCZ PRS in terms of sex, age, and topography. Findings reveal that polygenic risk for SCZ is robustly associated with increased functional neural connectivity among young adults without a SCZ diagnosis. Striking differences were observed between men and women throughout development, mapping onto key periods of risk for the onset of psychotic illness and underlining the critical importance of examining sex differences in associations with neuropsychiatric PRS across development.

scholarly journals Examining sex differences in neurodevelopmental and psychiatric genetic risk in anxiety and depression

2021 ◽  
Author(s):  
Joanna Martin ◽  
Kimiya Asjadi ◽  
Leon Hubbard ◽  
Kimberley Kendall ◽  
Antonio F. Pardiñas ◽  
...  
Keyword(s):  
Mental Health ◽  
Sex Differences ◽  
Family History ◽  
Psychiatric Disorders ◽  
Genetic Risk ◽  
Age At Onset ◽  
Anxiety And Depression ◽  
Rare Cnvs ◽  
Genetic Liability ◽  
History Of

AbstractAnxiety and depression are common mental health disorders and have a higher prevalence in females. They are modestly heritable, share genetic liability with other psychiatric disorders, and are highly heterogeneous. There is evidence that genetic liability to neurodevelopmental disorders, such as attention deficit hyperactivity disorder (ADHD) is associated with anxiety and depression, particularly in females. We investigated sex differences in family history for neurodevelopmental and psychiatric disorders and neurodevelopmental genetic risk burden (indexed by ADHD polygenic risk scores (PRS) and rare copy number variants; CNVs) in individuals with anxiety and depression, also taking into account age at onset.We used two complementary datasets: 1) participants with a self-reported diagnosis of anxiety or depression (N=4,178, 65.5% female; mean age=41.5 years; N=1,315 with genetic data) from the National Centre for Mental Health (NCMH) cohort and 2) a clinical sample of 13,273 (67.6% female; mean age=45.2 years) patients with major depressive disorder (MDD) from the Psychiatric Genomics Consortium (PGC). We tested for sex differences in family history of psychiatric problems and presence of rare CNVs (neurodevelopmental and >500kb loci) in NCMH only and for sex differences in ADHD PRS in both datasets.In the NCMH cohort, females were more likely to report family history of neurodevelopmental and psychiatric disorders, but there were no robust sex differences in ADHD PRS or presence of rare CNVs. There was weak evidence of higher ADHD PRS in females compared to males in the PGC MDD sample, particularly in those with an early onset of MDD.These results do not provide strong evidence of sex differences in neurodevelopmental genetic risk burden in adults with anxiety and depression. This indicates that sex may not be a major index of neurodevelopmental genetic heterogeneity, that is captured by ADHD PRS and rare CNV burden, in adults with anxiety and depression.

scholarly journals Towards clinical utility of polygenic risk scores

2019 ◽  
Vol 28 (R2) ◽  
pp. R133-R142 ◽  
Author(s):  
Samuel A Lambert ◽  
Gad Abraham ◽  
Michael Inouye
Keyword(s):  
Risk Factors ◽  
Family History ◽  
Risk Prediction ◽  
Clinical Utility ◽  
Disease Risk ◽  
Risk Scores ◽  
Polygenic Risk ◽  
Common Diseases ◽  
History Of Disease ◽  
History Of

Abstract Prediction of disease risk is an essential part of preventative medicine, often guiding clinical management. Risk prediction typically includes risk factors such as age, sex, family history of disease and lifestyle (e.g. smoking status); however, in recent years, there has been increasing interest to include genomic information into risk models. Polygenic risk scores (PRS) aggregate the effects of many genetic variants across the human genome into a single score and have recently been shown to have predictive value for multiple common diseases. In this review, we summarize the potential use cases for seven common diseases (breast cancer, prostate cancer, coronary artery disease, obesity, type 1 diabetes, type 2 diabetes and Alzheimer’s disease) where PRS has or could have clinical utility. PRS analysis for these diseases frequently revolved around (i) risk prediction performance of a PRS alone and in combination with other non-genetic risk factors, (ii) estimation of lifetime risk trajectories, (iii) the independent information of PRS and family history of disease or monogenic mutations and (iv) estimation of the value of adding a PRS to specific clinical risk prediction scenarios. We summarize open questions regarding PRS usability, ancestry bias and transferability, emphasizing the need for the next wave of studies to focus on the implementation and health-economic value of PRS testing. In conclusion, it is becoming clear that PRS have value in disease risk prediction and there are multiple areas where this may have clinical utility.

scholarly journals Dissecting clinical heterogeneity of bipolar disorder using multiple polygenic risk scores

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Brandon J. Coombes ◽  
Matej Markota ◽  
J. John Mann ◽  
Colin Colby ◽  
Eli Stahl ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Psychiatric Disorders ◽  
Suicide Attempts ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Rapid Cycling ◽  
Clinical Heterogeneity ◽  
Polygenic Risk ◽  
Clinical Observations ◽  
History Of

Abstract Bipolar disorder (BD) has high clinical heterogeneity, frequent psychiatric comorbidities, and elevated suicide risk. To determine genetic differences between common clinical sub-phenotypes of BD, we performed a systematic polygenic risk score (PRS) analysis using multiple PRSs from a range of psychiatric, personality, and lifestyle traits to dissect differences in BD sub-phenotypes in two BD cohorts: the Mayo Clinic BD Biobank (N = 968) and Genetic Association Information Network (N = 1001). Participants were assessed for history of psychosis, early-onset BD, rapid cycling (defined as four or more episodes in a year), and suicide attempts using questionnaires and the Structured Clinical Interview for DSM-IV. In a combined sample of 1969 bipolar cases (45.5% male), those with psychosis had higher PRS for SCZ (OR = 1.3 per S.D.; p = 3e-5) but lower PRSs for anhedonia (OR = 0.87; p = 0.003) and BMI (OR = 0.87; p = 0.003). Rapid cycling cases had higher PRS for ADHD (OR = 1.23; p = 7e-5) and MDD (OR = 1.23; p = 4e-5) and lower BD PRS (OR = 0.8; p = 0.004). Cases with a suicide attempt had higher PRS for MDD (OR = 1.26; p = 1e-6) and anhedonia (OR = 1.22; p = 2e-5) as well as lower PRS for educational attainment (OR = 0.87; p = 0.003). The observed novel PRS associations with sub-phenotypes align with clinical observations such as rapid cycling BD patients having a greater lifetime prevalence of ADHD. Our findings confirm that genetic heterogeneity contributes to clinical heterogeneity of BD and consideration of genetic contribution to psychopathologic components of psychiatric disorders may improve genetic prediction of complex psychiatric disorders.

scholarly journals Childhood maltreatment, prefrontal-paralimbic gray matter volume, and substance use in young adults and interactions with risk for bipolar disorder

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Dylan E. Kirsch ◽  
Valeria Tretyak ◽  
Sepeadeh Radpour ◽  
Wade A. Weber ◽  
Charles B. Nemeroff ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Substance Use ◽  
Young Adults ◽  
Family History ◽  
Childhood Maltreatment ◽  
Gray Matter Volume ◽  
Familial Risk ◽  
Cannabis Use ◽  
Typically Developing ◽  
History Of

AbstractChildhood maltreatment is associated with adverse effects on the brain, and an increased risk for psychopathology, including mood and substance use disorders. Individuals vary on the degree to which they exhibit neurobiological and clinical differences following maltreatment. Individuals with bipolar disorder exhibit greater magnitude of maltreatment-related prefrontal-paralimbic gray matter volume (GMV) deficits compared to typically developing individuals. It is unclear if greater structural differences stem from greater neural vulnerability to maltreatment in bipolar disorder, or if they relate to presence of other clinical features associated with childhood maltreatment, e.g., elevated prevalence of comorbid substance use disorders. To investigate this, we compared young adults with a family history of bipolar disorder (n = 21), but who did not fulfill diagnostic criteria for bipolar disorder, with typically developing young adults without a family history of bipolar disorder (n = 26). Participants completed structural neuroimaging, clinical and family history interviews, and assessment of childhood maltreatment and recent alcohol and cannabis use patterns. We examined relations between childhood maltreatment and prefrontal-paralimbic GMV by modeling main effects of maltreatment and family history group by maltreatment interactions on prefrontal-paralimbic GMV. We also examined relations between maltreatment and associated GMV changes with recent alcohol and cannabis use. Childhood maltreatment correlated with lower ventral, rostral and dorsolateral prefrontal and insular cortical GMV across all participants regardless of the presence or absence of familial history of bipolar disorder. However, exploratory analyses did reveal greater maltreatment-related GMV differences in individuals with prodromal symptoms of depression. Lower insula GMV was associated with greater frequency of cannabis use across all participants and greater quantity of alcohol use only in those with familial risk for bipolar disorder. Results suggest familial risk for bipolar disorder, and presumably genetic risk, may relate to outcomes following childhood maltreatment and should be considered in prevention/early intervention strategies.

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