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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.
A polymorphism of serotonin transporter was studied in 226 patients with affective disorders (n = 132 for bipolar, n = 94 for unipolar affective disorder) and in 213 healthy subjects. Consensus diagnosis by at least two psychiatrists, according to the ICD-10 and DSM-IV criteria was made for each patient using SCID (Structured Clinical Interview for DSM-IV Axis I Disorders). A functional polymorphism in the promoter region of serotonin transporter gene, where 44 bp are either inserted (long allele) or deleted (short allele) was analysed. Genotype s/s was significantly more frequent in patients comparing to the control group (P = 0.011 for bipolar and P = 0.003 for unipolar affective disorder) - the most marked association was found in males with bipolar and unipolar illness. The allele frequencies also differ significantly between patients and controls (P = 0.003 for bipolar and P = 0.001 for unipolar affective disorder). The frequency of the low activity (short) allele was higher in patients than in controls (51.1% in bipolar, and 54.3 in unipolar vs 39.4% in controls). We suggest that the presence of allele s may increase the susceptibility to occurrence of affective disorder.
There have been conflicting reports on whether the length polymorphism in
the promoter of the serotonin transporter gene (5-HTTLPR) moderates the
antidepressant effects of selective serotonin reuptake inhibitors
(SSRIs). We hypothesised that the pharmacogenetic effect of 5-HTTLPR is
modulated by gender, age and other variants in the serotonin transporter
To test the hypothesis that the 5-HTTLPR differently influences response
to escitalopram (an SSRI) compared with nortriptyline (a noradrenaline
The 5-HTTLPR and 13 additional markers across the serotonin transporter
gene were genotyped in 795 adults with moderate-to-severe depression
treated with escitalopram or nortriptyline in the Genome Based
Therapeutic Drugs for Depression (GENDEP) project.
The 5-HTTLPR moderated the response to escitalopram, with long-allele
carriers improving more than short-allele homozygotes. A significant
three-way interaction between 5-HTTLPR, drug and gender indicated that
the effect was concentrated in males treated with escitalopram. The
single-nucleotide polymorphism rs2020933 also influenced outcome.
The effect of 5-HTTLPR on antidepressant response is SSRI specific
conditional on gender and modulated by another polymorphism at the 5' end
of the serotonin transporter gene.
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