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Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.
To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.
This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.
The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.
Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.
Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.
To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.
Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.
Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.
AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.
Dean F. MacKinnon, Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA,
J. Raymond DePaulo, Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
Depression refers in the medical setting to clinically significant but transient emotional states which are called adjustment disorders and also to a clinical syndrome called major depression which occurs in unipolar depressive disorder and bipolar disorders. Confusion of adjustment disorders with depressive syndromes plagues both medical care and reasoning about mechanisms. Once identified, mood disorders (unipolar and bipolar disorders) are treated quite successfully with any of several medications and/or psychotherapy. The pathophysiology of mood disorders remains obscure, but clues are emerging as to the neuroanatomic components, molecular systems and genes involved in the vulnerability to mood disorder. The cumulative effect of these developments on a number of scientific fronts will be to unravel the complex knot of etiologic factors, leading to the refinement of current empirical treatment and the development of rational treatment. When we can identify the mechanisms of mood disorder, we will also gain an improved perspective from which to understand the role of environmental factors in the development of depressive and manic disorders.
In the official diagnostic nomenclature of American psychiatry a transition from the term ‘affective disorders’ to ‘mood disorders’ was made in 1987, though the diagnostic criteria for major depression and mania did not change appreciably. We use the term mood to denote a persistent emotional state, and affect or affective to refer to a constellation of phenomena generally associated with and including mood. We will use the term depression, hereafter, only to denote the syndrome of depressive illness.
Mood disorders are among the most common illnesses in the community and in the medical clinic. Depression, in avariety of community samples worldwide, affects as many as one in six individuals in the course of a lifetime (Doris et al., 1999). Mania occurs in 1–2% of the population. Ten to twenty per cent of patients screened in a primary care clinic have a major depressive disorder (Zung et al., 1993); depression was found in over one-quarter of patients in a neurology practice (Carson et al., 2000). Mania is less often a presenting problem for non-psychiatric physicians, but can occur as an iatrogenic complication from the use of antidepressants (Benazzi, 1997), corticosteroids (Sharfstein et al., 1982), or psychostimulants (Masand et al., 1995). Moreover, a number of medical conditions are associated with the syndromes of mania and depression, as will be described below.
Two psychiatric screening instruments, the Mini-Mental State (MMS), a test for cognitive disturbance, and the General Health Questionnaire (GHQ), were administered to 197 neurological in-patients. The results suggest a high rate of psychiatric disturbance. The highest rate of cognitive disturbance detected by the MMS was found in patients with Parkinson's disease. The highest rates of emotional disturbance indicated by GHQ scores were found in patients with myasthenia gravis and multiple sclerosis. MMS scores but not GHQ scores were related to standardtests of cognition, the diagnosis of cerebral pathology, and CAT scan abnormality. The results also demonstrate that the GHQ does not adequately detect patients with cognitive impairment. It is concluded that in populations at high risk for cognitive impairment a tandem screening procedure utilizing tests for both cognitive and emotional disorders is needed.
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